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1,818 | gui | https://github.com/beeware/toga | ['toolkit', 'gui'] | null | [] | [] | null | null | null | beeware/toga | toga | 3,998 | 673 | 85 | Python | https://toga.readthedocs.io/en/latest/ | A Python native, OS native GUI toolkit. | beeware | 2024-01-13 | 2014-08-01 | 495 | 8.067455 | https://avatars.githubusercontent.com/u/19795701?v=4 | A Python native, OS native GUI toolkit. | [] | ['gui', 'toolkit'] | 2024-01-11 | [('hoffstadt/dearpygui', 0.7974780201911926, 'gui', 2), ('kivy/kivy', 0.692936360836029, 'util', 0), ('parthjadhav/tkinter-designer', 0.6891065239906311, 'gui', 1), ('r0x0r/pywebview', 0.6624377965927124, 'gui', 1), ('urwid/urwid', 0.6368706822395325, 'term', 0), ('wxwidgets/phoenix', 0.6360959410667419, 'gui', 1), ('d... | 256 | 7 | null | 35.79 | 200 | 127 | 115 | 0 | 4 | 7 | 4 | 200 | 486 | 90 | 2.4 | 58 |
748 | ml | https://github.com/marqo-ai/marqo | [] | null | [] | [] | null | null | null | marqo-ai/marqo | marqo | 3,856 | 162 | 35 | Python | https://www.marqo.ai/ | Vector search for humans. Also available on cloud - cloud.marqo.ai | marqo-ai | 2024-01-13 | 2022-08-01 | 78 | 49.345521 | https://avatars.githubusercontent.com/u/103185353?v=4 | Vector search for humans. Also available on cloud - cloud.marqo.ai | ['chatgpt', 'clip', 'deep-learning', 'gpt', 'hnsw', 'information-retrieval', 'knn', 'large-language-models', 'machine-learning', 'machinelearning', 'multi-modal', 'natural-language-processing', 'search-engine', 'semantic-search', 'tensor-search', 'transformers', 'vector-search', 'vision-language', 'visual-search'] | ['chatgpt', 'clip', 'deep-learning', 'gpt', 'hnsw', 'information-retrieval', 'knn', 'large-language-models', 'machine-learning', 'machinelearning', 'multi-modal', 'natural-language-processing', 'search-engine', 'semantic-search', 'tensor-search', 'transformers', 'vector-search', 'vision-language', 'visual-search'] | 2024-01-11 | [('qdrant/qdrant', 0.7367421984672546, 'data', 4), ('cheshire-cat-ai/core', 0.6071776151657104, 'llm', 1), ('activeloopai/deeplake', 0.6008663177490234, 'ml-ops', 4), ('milvus-io/bootcamp', 0.5712332725524902, 'data', 1), ('googlecloudplatform/vertex-ai-samples', 0.5693247318267822, 'ml', 0), ('docarray/docarray', 0.56... | 30 | 2 | null | 7.23 | 115 | 93 | 18 | 0 | 18 | 17 | 18 | 115 | 33 | 90 | 0.3 | 58 |
429 | viz | https://github.com/holoviz/panel | [] | null | [] | [] | null | null | null | holoviz/panel | panel | 3,647 | 420 | 53 | Python | https://panel.holoviz.org | Panel: The powerful data exploration & web app framework for Python | holoviz | 2024-01-14 | 2018-08-23 | 283 | 12.854481 | https://avatars.githubusercontent.com/u/51678735?v=4 | Panel: The powerful data exploration & web app framework for Python | ['bokeh', 'control-panels', 'dashboards', 'dataapp', 'datascience', 'dataviz', 'gui', 'holoviews', 'holoviz', 'hvplot', 'jupyter', 'matplotlib', 'panel', 'plotly'] | ['bokeh', 'control-panels', 'dashboards', 'dataapp', 'datascience', 'dataviz', 'gui', 'holoviews', 'holoviz', 'hvplot', 'jupyter', 'matplotlib', 'panel', 'plotly'] | 2024-01-13 | [('plotly/dash', 0.7759690284729004, 'viz', 2), ('bokeh/bokeh', 0.7603949308395386, 'viz', 2), ('holoviz/holoviz', 0.7308956384658813, 'viz', 4), ('man-group/dtale', 0.7240487337112427, 'viz', 0), ('plotly/plotly.py', 0.7203231453895569, 'viz', 1), ('kanaries/pygwalker', 0.6920881271362305, 'pandas', 2), ('holoviz/hvpl... | 156 | 3 | null | 19.56 | 717 | 455 | 66 | 0 | 19 | 102 | 19 | 714 | 1,170 | 90 | 1.6 | 58 |
221 | jupyter | https://github.com/jupyterlite/jupyterlite | [] | null | [] | [] | null | null | null | jupyterlite/jupyterlite | jupyterlite | 3,470 | 258 | 40 | TypeScript | https://jupyterlite.rtfd.io/en/stable/try/lab | Wasm powered Jupyter running in the browser 💡 | jupyterlite | 2024-01-10 | 2021-03-27 | 148 | 23.378248 | https://avatars.githubusercontent.com/u/81094398?v=4 | Wasm powered Jupyter running in the browser 💡 | ['jupyter', 'jupyterlab', 'jupyterlab-extension', 'lite', 'pyodide', 'wasm', 'webassembly'] | ['jupyter', 'jupyterlab', 'jupyterlab-extension', 'lite', 'pyodide', 'wasm', 'webassembly'] | 2024-01-10 | [('voila-dashboards/voila', 0.6913954615592957, 'jupyter', 2), ('jupyterlab/jupyterlab', 0.6288254261016846, 'jupyter', 2), ('jupyterlab/jupyterlab-desktop', 0.6264117956161499, 'jupyter', 2), ('jupyter/notebook', 0.6035483479499817, 'jupyter', 1), ('jupyter-widgets/ipywidgets', 0.5854482650756836, 'jupyter', 1), ('pyo... | 56 | 5 | null | 3.04 | 84 | 52 | 34 | 0 | 22 | 493 | 22 | 84 | 156 | 90 | 1.9 | 58 |
1,013 | llm | https://github.com/whitead/paper-qa | [] | null | [] | [] | 1 | null | null | whitead/paper-qa | paper-qa | 3,383 | 321 | 43 | Python | null | LLM Chain for answering questions from documents with citations | whitead | 2024-01-13 | 2023-02-05 | 51 | 65.963788 | null | LLM Chain for answering questions from documents with citations | ['chatgpt', 'nlp', 'question-answering'] | ['chatgpt', 'nlp', 'question-answering'] | 2023-12-07 | [('rlancemartin/auto-evaluator', 0.5889334678649902, 'llm', 1), ('princeton-nlp/alce', 0.5843133330345154, 'llm', 0), ('night-chen/toolqa', 0.54909348487854, 'llm', 1), ('explosion/spacy-llm', 0.5373473763465881, 'llm', 1), ('mooler0410/llmspracticalguide', 0.5275523066520691, 'study', 1), ('deepset-ai/haystack', 0.514... | 12 | 4 | null | 3.31 | 33 | 17 | 11 | 1 | 75 | 83 | 75 | 33 | 22 | 90 | 0.7 | 58 |
1,528 | llm | https://github.com/minimaxir/simpleaichat | [] | null | [] | [] | null | null | null | minimaxir/simpleaichat | simpleaichat | 3,227 | 210 | 34 | Python | null | Python package for easily interfacing with chat apps, with robust features and minimal code complexity. | minimaxir | 2024-01-12 | 2023-05-06 | 38 | 83.973978 | null | Python package for easily interfacing with chat apps, with robust features and minimal code complexity. | ['ai', 'chatgpt'] | ['ai', 'chatgpt'] | 2024-01-08 | [('embedchain/embedchain', 0.7047023773193359, 'llm', 2), ('run-llama/rags', 0.6775078177452087, 'llm', 1), ('togethercomputer/openchatkit', 0.6666284203529358, 'nlp', 0), ('killianlucas/open-interpreter', 0.6259564757347107, 'llm', 1), ('rcgai/simplyretrieve', 0.6199681162834167, 'llm', 0), ('cheshire-cat-ai/core', 0.... | 12 | 2 | null | 2.29 | 28 | 10 | 8 | 0 | 6 | 9 | 6 | 28 | 29 | 90 | 1 | 58 |
1,286 | data | https://github.com/docarray/docarray | [] | null | [] | [] | null | null | null | docarray/docarray | docarray | 2,620 | 216 | 45 | Python | https://docs.docarray.org/ | Represent, send, store and search multimodal data | docarray | 2024-01-14 | 2021-12-14 | 111 | 23.603604 | https://avatars.githubusercontent.com/u/117445116?v=4 | Represent, send, store and search multimodal data | ['cross-modal', 'data-structures', 'dataclass', 'deep-learning', 'docarray', 'elasticsearch', 'fastapi', 'machine-learning', 'multi-modal', 'multimodal', 'nearest-neighbor-search', 'nested-data', 'neural-search', 'protobuf', 'pydantic', 'pytorch', 'qdrant', 'semantic-search', 'weaviate'] | ['cross-modal', 'data-structures', 'dataclass', 'deep-learning', 'docarray', 'elasticsearch', 'fastapi', 'machine-learning', 'multi-modal', 'multimodal', 'nearest-neighbor-search', 'nested-data', 'neural-search', 'protobuf', 'pydantic', 'pytorch', 'qdrant', 'semantic-search', 'weaviate'] | 2024-01-02 | [('milvus-io/bootcamp', 0.677416205406189, 'data', 1), ('next-gpt/next-gpt', 0.5986325144767761, 'llm', 1), ('thilinarajapakse/simpletransformers', 0.5803972482681274, 'nlp', 0), ('nomic-ai/nomic', 0.5800225734710693, 'nlp', 0), ('activeloopai/deeplake', 0.5793482661247253, 'ml-ops', 3), ('neuml/txtai', 0.5759537816047... | 72 | 2 | null | 8.4 | 35 | 21 | 25 | 0 | 17 | 81 | 17 | 35 | 124 | 90 | 3.5 | 58 |
1,358 | gis | https://github.com/opengeos/segment-geospatial | [] | null | [] | [] | null | null | null | opengeos/segment-geospatial | segment-geospatial | 2,478 | 247 | 52 | Python | https://samgeo.gishub.org | A Python package for segmenting geospatial data with the Segment Anything Model (SAM) | opengeos | 2024-01-13 | 2023-04-19 | 40 | 60.65035 | https://avatars.githubusercontent.com/u/129896036?v=4 | A Python package for segmenting geospatial data with the Segment Anything Model (SAM) | ['artificial-intelligence', 'deep-learning', 'geopython', 'geospatial', 'machine-learning', 'segment-anything', 'segmentation'] | ['artificial-intelligence', 'deep-learning', 'geopython', 'geospatial', 'machine-learning', 'segment-anything', 'segmentation'] | 2023-12-07 | [('earthlab/earthpy', 0.5494171977043152, 'gis', 0), ('sentinel-hub/eo-learn', 0.5391361117362976, 'gis', 1), ('geopandas/geopandas', 0.5388274788856506, 'gis', 1), ('microsoft/torchgeo', 0.5342783331871033, 'gis', 2), ('osgeo/grass', 0.5276463627815247, 'gis', 2), ('residentmario/geoplot', 0.5210736989974976, 'gis', 0... | 11 | 4 | null | 2.94 | 22 | 12 | 9 | 1 | 22 | 30 | 22 | 22 | 36 | 90 | 1.6 | 58 |
859 | util | https://github.com/dosisod/refurb | [] | null | [] | [] | 1 | null | null | dosisod/refurb | refurb | 2,425 | 55 | 16 | Python | null | A tool for refurbishing and modernizing Python codebases | dosisod | 2024-01-10 | 2022-07-27 | 78 | 30.751812 | null | A tool for refurbishing and modernizing Python codebases | ['cli', 'gplv3', 'mypy', 'python310', 'testing'] | ['cli', 'gplv3', 'mypy', 'python310', 'testing'] | 2024-01-13 | [('pypa/hatch', 0.6656979322433472, 'util', 1), ('facebookincubator/bowler', 0.5965598225593567, 'util', 0), ('pypa/pipenv', 0.5785287618637085, 'util', 0), ('rubik/radon', 0.5743918418884277, 'util', 1), ('prompt-toolkit/ptpython', 0.573533296585083, 'util', 1), ('python-rope/rope', 0.5674479007720947, 'util', 0), ('p... | 16 | 7 | null | 2.67 | 33 | 28 | 18 | 0 | 20 | 25 | 20 | 33 | 61 | 90 | 1.8 | 58 |
1,809 | data | https://github.com/lancedb/lancedb | ['vectordb'] | null | [] | [] | null | null | null | lancedb/lancedb | lancedb | 1,903 | 113 | 19 | Python | https://lancedb.github.io/lancedb/ | Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps! | lancedb | 2024-01-14 | 2023-02-28 | 48 | 39.645833 | https://avatars.githubusercontent.com/u/108903835?v=4 | Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps! | ['approximate-nearest-neighbor-search', 'image-search', 'nearest-neighbor-search', 'recommender-system', 'search-engine', 'semantic-search', 'similarity-search', 'vector-database'] | ['approximate-nearest-neighbor-search', 'image-search', 'nearest-neighbor-search', 'recommender-system', 'search-engine', 'semantic-search', 'similarity-search', 'vector-database', 'vectordb'] | 2024-01-14 | [('activeloopai/deeplake', 0.7212356925010681, 'ml-ops', 1), ('qdrant/qdrant', 0.6593559384346008, 'data', 7), ('pathwaycom/llm-app', 0.6573936343193054, 'llm', 1), ('chroma-core/chroma', 0.6137559413909912, 'data', 1), ('jina-ai/vectordb', 0.612372100353241, 'data', 2), ('featureform/embeddinghub', 0.6071080565452576,... | 39 | 2 | null | 11.44 | 290 | 201 | 11 | 0 | 68 | 107 | 68 | 289 | 239 | 90 | 0.8 | 58 |
1,513 | llm | https://github.com/neulab/prompt2model | ['language-model', 'deployment'] | null | [] | [] | null | null | null | neulab/prompt2model | prompt2model | 1,768 | 152 | 23 | Python | null | prompt2model - Generate Deployable Models from Natural Language Instructions | neulab | 2024-01-13 | 2023-03-27 | 44 | 40.05178 | https://avatars.githubusercontent.com/u/22324665?v=4 | prompt2model - Generate Deployable Models from Natural Language Instructions | [] | ['deployment', 'language-model'] | 2024-01-12 | [('hazyresearch/ama_prompting', 0.687862753868103, 'llm', 0), ('keirp/automatic_prompt_engineer', 0.6848369836807251, 'llm', 1), ('1rgs/jsonformer', 0.6683309674263, 'llm', 0), ('guidance-ai/guidance', 0.6568854451179504, 'llm', 1), ('ctlllll/llm-toolmaker', 0.623613178730011, 'llm', 1), ('promptslab/promptify', 0.5863... | 13 | 6 | null | 3.19 | 33 | 18 | 10 | 0 | 9 | 11 | 9 | 33 | 56 | 90 | 1.7 | 58 |
1,873 | llm | https://github.com/llmware-ai/llmware | [] | null | [] | [] | null | null | null | llmware-ai/llmware | llmware | 1,744 | 141 | 29 | Python | https://pypi.org/project/llmware/ | Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models. | llmware-ai | 2024-01-14 | 2023-09-29 | 17 | 99.252033 | https://avatars.githubusercontent.com/u/145479774?v=4 | Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models. | ['ai', 'bert', 'embedding-vectors', 'embeddings', 'faiss', 'generative-ai', 'information-retrieval', 'large-language-models', 'machine-learning', 'milvus', 'nlp', 'parsing', 'pytorch', 'question-answering', 'rag', 'retrieval-augmented-generation', 'semantic-search', 'transformers'] | ['ai', 'bert', 'embedding-vectors', 'embeddings', 'faiss', 'generative-ai', 'information-retrieval', 'large-language-models', 'machine-learning', 'milvus', 'nlp', 'parsing', 'pytorch', 'question-answering', 'rag', 'retrieval-augmented-generation', 'semantic-search', 'transformers'] | 2024-01-10 | [('paddlepaddle/paddlenlp', 0.7560280561447144, 'llm', 4), ('neuml/txtai', 0.7031641602516174, 'nlp', 9), ('deepset-ai/haystack', 0.6901717185974121, 'llm', 11), ('intellabs/fastrag', 0.669150710105896, 'nlp', 6), ('explosion/spacy-llm', 0.6662053465843201, 'llm', 3), ('jina-ai/finetuner', 0.6378600597381592, 'ml', 1),... | 13 | 3 | null | 4.31 | 229 | 205 | 4 | 0 | 0 | 0 | 0 | 229 | 138 | 90 | 0.6 | 58 |
1,267 | perf | https://github.com/intel/intel-extension-for-transformers | [] | null | [] | [] | null | null | null | intel/intel-extension-for-transformers | intel-extension-for-transformers | 1,672 | 166 | 25 | C++ | null | ⚡ Build your chatbot within minutes on your favorite device; offer SOTA compression techniques for LLMs; run LLMs efficiently on Intel Platforms⚡ | intel | 2024-01-14 | 2022-11-11 | 63 | 26.301124 | https://avatars.githubusercontent.com/u/17888862?v=4 | ⚡ Build your chatbot within minutes on your favorite device; offer SOTA compression techniques for LLMs; run LLMs efficiently on Intel Platforms⚡ | ['4-bits', 'attention-sink', 'chatbot', 'chatpdf', 'cpu', 'gaudi2', 'gpu', 'habana', 'intel-optimized-llamacpp', 'large-language-model', 'llm-cpu', 'llm-inference', 'neural-chat', 'neural-chat-7b', 'neurips2023', 'pc', 'speculative-decoding', 'streamingllm', 'xeon'] | ['4-bits', 'attention-sink', 'chatbot', 'chatpdf', 'cpu', 'gaudi2', 'gpu', 'habana', 'intel-optimized-llamacpp', 'large-language-model', 'llm-cpu', 'llm-inference', 'neural-chat', 'neural-chat-7b', 'neurips2023', 'pc', 'speculative-decoding', 'streamingllm', 'xeon'] | 2024-01-13 | [('bigscience-workshop/petals', 0.7305524945259094, 'data', 1), ('nomic-ai/gpt4all', 0.7130550742149353, 'llm', 2), ('h2oai/h2o-llmstudio', 0.6861023902893066, 'llm', 1), ('pathwaycom/llm-app', 0.6731693148612976, 'llm', 1), ('deep-diver/llm-as-chatbot', 0.6634297966957092, 'llm', 1), ('hwchase17/langchain', 0.66289991... | 91 | 2 | null | 24.88 | 702 | 650 | 14 | 0 | 8 | 15 | 8 | 702 | 760 | 90 | 1.1 | 58 |
1,760 | term | https://github.com/tconbeer/harlequin | ['tool', 'sql', 'data'] | null | [] | [] | 1 | null | null | tconbeer/harlequin | harlequin | 1,637 | 30 | 12 | Python | https://harlequin.sh | The SQL IDE for Your Terminal. | tconbeer | 2024-01-14 | 2023-05-02 | 39 | 41.974359 | null | The SQL IDE for Your Terminal. | [] | ['data', 'sql', 'tool'] | 2024-01-12 | [('tconbeer/sqlfmt', 0.569164514541626, 'data', 1), ('tiangolo/sqlmodel', 0.569147527217865, 'data', 1), ('sqlalchemy/sqlalchemy', 0.5578516721725464, 'data', 1), ('simonw/sqlite-utils', 0.5377789735794067, 'data', 0), ('saulpw/visidata', 0.5237422585487366, 'term', 0), ('methexis-inc/terminal-copilot', 0.5151594877243... | 8 | 6 | null | 4.44 | 131 | 112 | 9 | 0 | 50 | 68 | 50 | 131 | 88 | 90 | 0.7 | 58 |
1,123 | ml-rl | https://github.com/pytorch/rl | ['reinforcement-learning'] | null | [] | [] | null | null | null | pytorch/rl | rl | 1,621 | 212 | 40 | Python | https://pytorch.org/rl | A modular, primitive-first, python-first PyTorch library for Reinforcement Learning. | pytorch | 2024-01-13 | 2022-02-01 | 104 | 15.586538 | https://avatars.githubusercontent.com/u/21003710?v=4 | A modular, primitive-first, python-first PyTorch library for Reinforcement Learning. | ['ai', 'control', 'decision-making', 'distributed-computing', 'machine-learning', 'marl', 'model-based-reinforcement-learning', 'multi-agent-reinforcement-learning', 'pytorch', 'reinforcement-learning', 'rl', 'robotics', 'torch'] | ['ai', 'control', 'decision-making', 'distributed-computing', 'machine-learning', 'marl', 'model-based-reinforcement-learning', 'multi-agent-reinforcement-learning', 'pytorch', 'reinforcement-learning', 'rl', 'robotics', 'torch'] | 2024-01-14 | [('thu-ml/tianshou', 0.7527033090591431, 'ml-rl', 2), ('denys88/rl_games', 0.7474822402000427, 'ml-rl', 2), ('tensorlayer/tensorlayer', 0.7300659418106079, 'ml-rl', 1), ('humancompatibleai/imitation', 0.6811489462852478, 'ml-rl', 0), ('deepmind/acme', 0.6701556444168091, 'ml-rl', 1), ('pytorch/ignite', 0.66546005010604... | 130 | 4 | null | 11.87 | 212 | 172 | 24 | 0 | 8 | 7 | 8 | 212 | 568 | 90 | 2.7 | 58 |
193 | template | https://github.com/tiangolo/full-stack-fastapi-postgresql | [] | null | [] | [] | null | null | null | tiangolo/full-stack-fastapi-postgresql | full-stack-fastapi-postgresql | 14,174 | 2,531 | 249 | TypeScript | null | Full stack, modern web application generator. Using FastAPI, PostgreSQL as database, Docker, automatic HTTPS and more. | tiangolo | 2024-01-14 | 2019-02-23 | 257 | 55.059933 | null | Full stack, modern web application generator. Using FastAPI, PostgreSQL as database, Docker, automatic HTTPS and more. | ['backend', 'celery', 'cookiecutter', 'docker', 'fastapi', 'frontend', 'json', 'json-schema', 'jwt', 'letsencrypt', 'openapi', 'openapi3', 'pgadmin', 'postgresql', 'swagger', 'traefik', 'vue', 'vuex'] | ['backend', 'celery', 'cookiecutter', 'docker', 'fastapi', 'frontend', 'json', 'json-schema', 'jwt', 'letsencrypt', 'openapi', 'openapi3', 'pgadmin', 'postgresql', 'swagger', 'traefik', 'vue', 'vuex'] | 2023-12-27 | [('tiangolo/fastapi', 0.6879447102546692, 'web', 6), ('piccolo-orm/piccolo_admin', 0.6423637866973877, 'data', 2), ('vitalik/django-ninja', 0.6353817582130432, 'web', 2), ('rawheel/fastapi-boilerplate', 0.6298112869262695, 'web', 3), ('aeternalis-ingenium/fastapi-backend-template', 0.6168069839477539, 'web', 4), ('huga... | 21 | 4 | null | 0.52 | 63 | 36 | 60 | 1 | 0 | 1 | 1 | 63 | 79 | 90 | 1.3 | 57 |
1,716 | util | https://github.com/google/yapf | ['code-quality'] | null | [] | [] | null | null | null | google/yapf | yapf | 13,543 | 958 | 214 | Python | null | A formatter for Python files | google | 2024-01-14 | 2015-03-18 | 462 | 29.259568 | https://avatars.githubusercontent.com/u/1342004?v=4 | A formatter for Python files | ['formatter', 'google'] | ['code-quality', 'formatter', 'google'] | 2023-11-08 | [('grantjenks/blue', 0.749129056930542, 'util', 2), ('hhatto/autopep8', 0.7038267850875854, 'util', 1), ('psf/black', 0.6890390515327454, 'util', 2), ('danielnoord/pydocstringformatter', 0.6070597171783447, 'util', 1), ('astral-sh/ruff', 0.6007269024848938, 'util', 1), ('pycqa/isort', 0.5961623191833496, 'util', 2), ('... | 151 | 4 | null | 2.19 | 39 | 14 | 107 | 2 | 0 | 8 | 8 | 39 | 46 | 90 | 1.2 | 57 |
1,045 | nlp | https://github.com/jina-ai/clip-as-service | [] | null | [] | [] | null | null | null | jina-ai/clip-as-service | clip-as-service | 12,043 | 2,056 | 217 | Python | https://clip-as-service.jina.ai | 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP | jina-ai | 2024-01-13 | 2018-11-12 | 272 | 44.252493 | https://avatars.githubusercontent.com/u/60539444?v=4 | 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP | ['bert', 'bert-as-service', 'clip-as-service', 'clip-model', 'cross-modal-retrieval', 'cross-modality', 'deep-learning', 'image2vec', 'multi-modality', 'neural-search', 'onnx', 'openai', 'pytorch', 'sentence-encoding', 'sentence2vec'] | ['bert', 'bert-as-service', 'clip-as-service', 'clip-model', 'cross-modal-retrieval', 'cross-modality', 'deep-learning', 'image2vec', 'multi-modality', 'neural-search', 'onnx', 'openai', 'pytorch', 'sentence-encoding', 'sentence2vec'] | 2023-12-20 | [('jina-ai/finetuner', 0.7554095387458801, 'ml', 2), ('ukplab/sentence-transformers', 0.7321420311927795, 'nlp', 0), ('rom1504/clip-retrieval', 0.6420944929122925, 'ml', 1), ('amansrivastava17/embedding-as-service', 0.6331066489219666, 'nlp', 4), ('openai/clip', 0.6114118695259094, 'ml-dl', 1), ('alibaba/easynlp', 0.60... | 66 | 4 | null | 0.31 | 16 | 7 | 63 | 1 | 2 | 24 | 2 | 16 | 32 | 90 | 2 | 57 |
598 | ml | https://github.com/cleanlab/cleanlab | [] | null | [] | [] | null | null | null | cleanlab/cleanlab | cleanlab | 7,697 | 619 | 79 | Python | https://cleanlab.ai | The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels. | cleanlab | 2024-01-13 | 2018-05-11 | 298 | 25.779426 | https://avatars.githubusercontent.com/u/90712480?v=4 | The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels. | ['active-learning', 'annotation', 'data-analysis', 'data-centric-ai', 'data-cleaning', 'data-curation', 'data-labeling', 'data-profiling', 'data-quality', 'data-science', 'data-validation', 'dataops', 'dataquality', 'datasets', 'labeling', 'llms', 'noisy-labels', 'out-of-distribution-detection', 'outlier-detection', 'w... | ['active-learning', 'annotation', 'data-analysis', 'data-centric-ai', 'data-cleaning', 'data-curation', 'data-labeling', 'data-profiling', 'data-quality', 'data-science', 'data-validation', 'dataops', 'dataquality', 'datasets', 'labeling', 'llms', 'noisy-labels', 'out-of-distribution-detection', 'outlier-detection', 'w... | 2024-01-12 | [('ydataai/ydata-quality', 0.583878219127655, 'data', 0), ('whylabs/whylogs', 0.5660983324050903, 'util', 3), ('doccano/doccano', 0.5571958422660828, 'nlp', 2), ('csinva/imodels', 0.5562312602996826, 'ml', 1), ('netflix/metaflow', 0.5494846105575562, 'ml-ops', 1), ('alirezadir/machine-learning-interview-enlightener', 0... | 44 | 3 | null | 5.56 | 135 | 69 | 69 | 0 | 4 | 2 | 4 | 135 | 157 | 90 | 1.2 | 57 |
552 | ml-dl | https://github.com/arogozhnikov/einops | [] | null | [] | [] | null | null | null | arogozhnikov/einops | einops | 7,548 | 328 | 69 | Python | https://einops.rocks | Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others) | arogozhnikov | 2024-01-13 | 2018-09-22 | 279 | 27.01227 | null | Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others) | ['chainer', 'cupy', 'deep-learning', 'einops', 'jax', 'keras', 'numpy', 'pytorch', 'tensor', 'tensorflow'] | ['chainer', 'cupy', 'deep-learning', 'einops', 'jax', 'keras', 'numpy', 'pytorch', 'tensor', 'tensorflow'] | 2024-01-11 | [('tensorly/tensorly', 0.7486700415611267, 'ml-dl', 6), ('ggerganov/ggml', 0.674818754196167, 'ml', 0), ('intel/intel-extension-for-pytorch', 0.6702998876571655, 'perf', 2), ('rafiqhasan/auto-tensorflow', 0.6536889672279358, 'ml-dl', 1), ('huggingface/transformers', 0.6441165804862976, 'nlp', 4), ('patrick-kidger/torch... | 26 | 8 | null | 1.92 | 16 | 10 | 65 | 0 | 5 | 2 | 5 | 16 | 22 | 90 | 1.4 | 57 |
1,142 | util | https://github.com/eternnoir/pytelegrambotapi | [] | null | [] | [] | null | null | null | eternnoir/pytelegrambotapi | pyTelegramBotAPI | 7,429 | 1,975 | 225 | Python | null | Python Telegram bot api. | eternnoir | 2024-01-14 | 2015-06-26 | 448 | 16.561465 | null | Python Telegram bot api. | ['bot-api', 'python-api', 'telegram', 'telegram-bot', 'telegram-bot-api'] | ['bot-api', 'python-api', 'telegram', 'telegram-bot', 'telegram-bot-api'] | 2024-01-12 | [('mitmproxy/pdoc', 0.5450152158737183, 'util', 0), ('openai/gpt-discord-bot', 0.5340373516082764, 'llm', 0), ('pdoc3/pdoc', 0.5075708031654358, 'util', 0), ('hugapi/hug', 0.507483184337616, 'util', 1), ('freqtrade/freqtrade', 0.5027558207511902, 'crypto', 1), ('minimaxir/simpleaichat', 0.5022081732749939, 'llm', 0), (... | 228 | 2 | null | 4 | 66 | 63 | 104 | 0 | 7 | 8 | 7 | 67 | 200 | 90 | 3 | 57 |
409 | web | https://github.com/encode/uvicorn | [] | null | [] | [] | null | null | null | encode/uvicorn | uvicorn | 7,420 | 685 | 91 | Python | https://www.uvicorn.org/ | An ASGI web server, for Python. 🦄 | encode | 2024-01-14 | 2017-05-31 | 347 | 21.330595 | https://avatars.githubusercontent.com/u/19159390?v=4 | An ASGI web server, for Python. 🦄 | ['asgi', 'asyncio', 'http', 'http-server'] | ['asgi', 'asyncio', 'http', 'http-server'] | 2024-01-03 | [('neoteroi/blacksheep', 0.8586666584014893, 'web', 4), ('encode/httpx', 0.8501601815223694, 'web', 2), ('pallets/quart', 0.8250173926353455, 'web', 3), ('aio-libs/aiohttp', 0.7939640879631042, 'web', 3), ('encode/starlette', 0.6668508052825928, 'web', 1), ('falconry/falcon', 0.6588360667228699, 'web', 2), ('klen/muffi... | 174 | 4 | null | 2.46 | 70 | 45 | 81 | 0 | 9 | 23 | 9 | 70 | 69 | 90 | 1 | 57 |
770 | util | https://github.com/google/latexify_py | [] | null | [] | [] | null | null | null | google/latexify_py | latexify_py | 6,714 | 366 | 56 | Python | null | A library to generate LaTeX expression from Python code. | google | 2024-01-13 | 2020-07-25 | 183 | 36.602804 | https://avatars.githubusercontent.com/u/1342004?v=4 | A library to generate LaTeX expression from Python code. | [] | [] | 2023-12-08 | [('connorferster/handcalcs', 0.7623890042304993, 'jupyter', 0), ('pytoolz/toolz', 0.6760282516479492, 'util', 0), ('julienpalard/pipe', 0.5925378799438477, 'util', 0), ('google/yapf', 0.5899499654769897, 'util', 0), ('pyston/pyston', 0.5858403444290161, 'util', 0), ('python/cpython', 0.5829751491546631, 'util', 0), ('p... | 29 | 5 | null | 0.27 | 24 | 21 | 42 | 1 | 6 | 4 | 6 | 24 | 55 | 90 | 2.3 | 57 |
1,451 | util | https://github.com/conda/conda | ['package-manager', 'packaging'] | null | [] | [] | null | null | null | conda/conda | conda | 5,923 | 1,467 | 197 | Python | https://docs.conda.io/projects/conda/ | A system-level, binary package and environment manager running on all major operating systems and platforms. | conda | 2024-01-14 | 2012-10-15 | 589 | 10.053589 | https://avatars.githubusercontent.com/u/6392739?v=4 | A system-level, binary package and environment manager running on all major operating systems and platforms. | ['conda', 'package-management'] | ['conda', 'package-management', 'package-manager', 'packaging'] | 2024-01-12 | [('mamba-org/mamba', 0.752036988735199, 'util', 3), ('spack/spack', 0.7269142270088196, 'util', 1), ('pomponchik/instld', 0.6547331809997559, 'util', 1), ('indygreg/pyoxidizer', 0.5986080169677734, 'util', 2), ('conda/conda-build', 0.5913727283477783, 'util', 2), ('mamba-org/quetz', 0.5807616710662842, 'util', 1), ('mi... | 448 | 3 | null | 14.12 | 767 | 573 | 137 | 0 | 14 | 26 | 14 | 767 | 832 | 90 | 1.1 | 57 |
1,889 | ml | https://github.com/kevinmusgrave/pytorch-metric-learning | ['pytorch', 'embeddings'] | null | [] | [] | null | null | null | kevinmusgrave/pytorch-metric-learning | pytorch-metric-learning | 5,618 | 646 | 65 | Python | https://kevinmusgrave.github.io/pytorch-metric-learning/ | The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch. | kevinmusgrave | 2024-01-14 | 2019-10-23 | 222 | 25.208974 | null | The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch. | ['computer-vision', 'contrastive-learning', 'deep-learning', 'deep-metric-learning', 'embeddings', 'image-retrieval', 'machine-learning', 'metric-learning', 'pytorch', 'self-supervised-learning'] | ['computer-vision', 'contrastive-learning', 'deep-learning', 'deep-metric-learning', 'embeddings', 'image-retrieval', 'machine-learning', 'metric-learning', 'pytorch', 'self-supervised-learning'] | 2023-12-16 | [('oml-team/open-metric-learning', 0.7173192501068115, 'ml', 5), ('roboflow/supervision', 0.6149064302444458, 'ml', 4), ('scikit-learn-contrib/metric-learn', 0.5882241129875183, 'ml', 2), ('qdrant/quaterion', 0.584888219833374, 'ml', 5), ('lightly-ai/lightly', 0.581474244594574, 'ml', 7), ('tensorflow/tensorflow', 0.55... | 40 | 6 | null | 2.56 | 24 | 18 | 51 | 1 | 13 | 12 | 13 | 24 | 54 | 90 | 2.2 | 57 |
354 | ml-ops | https://github.com/feast-dev/feast | [] | null | [] | [] | null | null | null | feast-dev/feast | feast | 5,029 | 896 | 69 | Python | https://feast.dev | Feature Store for Machine Learning | feast-dev | 2024-01-14 | 2018-12-10 | 268 | 18.754928 | https://avatars.githubusercontent.com/u/57027613?v=4 | Feature Store for Machine Learning | ['big-data', 'data-engineering', 'data-quality', 'data-science', 'feature-store', 'features', 'machine-learning', 'ml', 'mlops'] | ['big-data', 'data-engineering', 'data-quality', 'data-science', 'feature-store', 'features', 'machine-learning', 'ml', 'mlops'] | 2024-01-13 | [('featureform/embeddinghub', 0.7385993599891663, 'nlp', 6), ('polyaxon/polyaxon', 0.6851301193237305, 'ml-ops', 4), ('netflix/metaflow', 0.6503940224647522, 'ml-ops', 4), ('firmai/industry-machine-learning', 0.6406149864196777, 'study', 2), ('kubeflow/pipelines', 0.6390533447265625, 'ml-ops', 3), ('onnx/onnx', 0.63267... | 222 | 4 | null | 3.38 | 118 | 52 | 62 | 0 | 13 | 27 | 13 | 117 | 126 | 90 | 1.1 | 57 |
227 | ml | https://github.com/online-ml/river | [] | null | [] | [] | 1 | null | null | online-ml/river | river | 4,605 | 551 | 85 | Python | https://riverml.xyz | 🌊 Online machine learning in Python | online-ml | 2024-01-13 | 2019-01-24 | 261 | 17.595524 | https://avatars.githubusercontent.com/u/47002673?v=4 | 🌊 Online machine learning in Python | ['concept-drift', 'data-science', 'incremental-learning', 'machine-learning', 'online-learning', 'online-machine-learning', 'online-statistics', 'real-time-processing', 'stream-processing', 'streaming', 'streaming-data'] | ['concept-drift', 'data-science', 'incremental-learning', 'machine-learning', 'online-learning', 'online-machine-learning', 'online-statistics', 'real-time-processing', 'stream-processing', 'streaming', 'streaming-data'] | 2024-01-01 | [('scikit-learn/scikit-learn', 0.6860164403915405, 'ml', 2), ('jeshraghian/snntorch', 0.615203320980072, 'ml-dl', 1), ('gradio-app/gradio', 0.6122671961784363, 'viz', 2), ('ddbourgin/numpy-ml', 0.6021139025688171, 'ml', 1), ('xplainable/xplainable', 0.584074079990387, 'ml-interpretability', 2), ('pycaret/pycaret', 0.57... | 108 | 6 | null | 5.67 | 137 | 31 | 61 | 0 | 7 | 7 | 7 | 137 | 161 | 90 | 1.2 | 57 |
887 | time-series | https://github.com/awslabs/gluonts | [] | null | [] | [] | null | null | null | awslabs/gluonts | gluonts | 4,008 | 758 | 74 | Python | https://ts.gluon.ai | Probabilistic time series modeling in Python | awslabs | 2024-01-12 | 2019-05-15 | 245 | 16.30215 | https://avatars.githubusercontent.com/u/3299148?v=4 | Probabilistic time series modeling in Python | ['artificial-intelligence', 'aws', 'data-science', 'deep-learning', 'forecasting', 'machine-learning', 'mxnet', 'neural-networks', 'pytorch', 'sagemaker', 'time-series', 'time-series-forecasting', 'time-series-prediction', 'timeseries', 'torch'] | ['artificial-intelligence', 'aws', 'data-science', 'deep-learning', 'forecasting', 'machine-learning', 'mxnet', 'neural-networks', 'pytorch', 'sagemaker', 'time-series', 'time-series-forecasting', 'time-series-prediction', 'timeseries', 'torch'] | 2024-01-10 | [('firmai/atspy', 0.695907711982727, 'time-series', 2), ('alkaline-ml/pmdarima', 0.6824057102203369, 'time-series', 3), ('unit8co/darts', 0.6495864987373352, 'time-series', 5), ('uber/orbit', 0.6446792483329773, 'time-series', 4), ('rjt1990/pyflux', 0.623365581035614, 'time-series', 1), ('scikit-learn/scikit-learn', 0.... | 110 | 5 | null | 5.29 | 96 | 63 | 57 | 0 | 34 | 23 | 34 | 96 | 130 | 90 | 1.4 | 57 |
1,608 | llm | https://github.com/openbmb/toolbench | ['instruction-tuning', 'evaluation'] | null | [] | [] | null | null | null | openbmb/toolbench | ToolBench | 3,959 | 336 | 49 | Python | https://openbmb.github.io/ToolBench/ | An open platform for training, serving, and evaluating large language model for tool learning. | openbmb | 2024-01-14 | 2023-05-28 | 35 | 112.198381 | https://avatars.githubusercontent.com/u/89920203?v=4 | An open platform for training, serving, and evaluating large language model for tool learning. | [] | ['evaluation', 'instruction-tuning'] | 2023-11-22 | [('lm-sys/fastchat', 0.7016268968582153, 'llm', 1), ('ai21labs/lm-evaluation', 0.6778345704078674, 'llm', 0), ('conceptofmind/toolformer', 0.6644108891487122, 'llm', 0), ('ctlllll/llm-toolmaker', 0.6306527853012085, 'llm', 0), ('night-chen/toolqa', 0.6098852753639221, 'llm', 0), ('lucidrains/toolformer-pytorch', 0.5833... | 16 | 3 | null | 2.83 | 63 | 24 | 8 | 2 | 0 | 0 | 0 | 63 | 63 | 90 | 1 | 57 |
1,770 | typing | https://github.com/python/typeshed | ['code-quality'] | null | [] | [] | null | null | null | python/typeshed | typeshed | 3,908 | 1,680 | 78 | Python | null | Collection of library stubs for Python, with static types | python | 2024-01-13 | 2015-03-05 | 464 | 8.409468 | https://avatars.githubusercontent.com/u/1525981?v=4 | Collection of library stubs for Python, with static types | ['stub', 'types', 'typing'] | ['code-quality', 'stub', 'types', 'typing'] | 2024-01-12 | [('instagram/monkeytype', 0.723702609539032, 'typing', 1), ('google/pytype', 0.7091848254203796, 'typing', 3), ('python/mypy', 0.6911789178848267, 'typing', 3), ('microsoft/pyright', 0.6651108264923096, 'typing', 1), ('pytoolz/toolz', 0.5580030083656311, 'util', 0), ('facebook/pyre-check', 0.5521007180213928, 'typing',... | 1,367 | 5 | null | 22.35 | 463 | 365 | 108 | 0 | 0 | 0 | 0 | 463 | 1,257 | 90 | 2.7 | 57 |
269 | web | https://github.com/strawberry-graphql/strawberry | [] | null | [] | [] | null | null | null | strawberry-graphql/strawberry | strawberry | 3,613 | 484 | 44 | Python | https://strawberry.rocks | A GraphQL library for Python that leverages type annotations 🍓 | strawberry-graphql | 2024-01-13 | 2018-12-21 | 266 | 13.553591 | https://avatars.githubusercontent.com/u/48071860?v=4 | A GraphQL library for Python that leverages type annotations 🍓 | ['asgi', 'asyncio', 'django', 'graphql', 'graphql-library', 'graphql-schema', 'graphql-server', 'mypy', 'starlette', 'strawberry'] | ['asgi', 'asyncio', 'django', 'graphql', 'graphql-library', 'graphql-schema', 'graphql-server', 'mypy', 'starlette', 'strawberry'] | 2024-01-07 | [('instagram/monkeytype', 0.6149357557296753, 'typing', 0), ('patrick-kidger/torchtyping', 0.5875641703605652, 'typing', 0), ('facebook/pyre-check', 0.5584018230438232, 'typing', 0), ('accenture/ampligraph', 0.5520169734954834, 'data', 0), ('tiangolo/sqlmodel', 0.5469264984130859, 'data', 0), ('jsonpickle/jsonpickle', ... | 237 | 5 | null | 9.63 | 643 | 186 | 62 | 0 | 164 | 131 | 164 | 643 | 664 | 90 | 1 | 57 |
1,092 | llm | https://github.com/eleutherai/lm-evaluation-harness | ['benchmark', 'evaluation', 'language-model'] | null | [] | [] | null | null | null | eleutherai/lm-evaluation-harness | lm-evaluation-harness | 3,589 | 921 | 34 | Python | https://www.eleuther.ai | A framework for few-shot evaluation of language models. | eleutherai | 2024-01-14 | 2020-08-28 | 178 | 20.0984 | https://avatars.githubusercontent.com/u/68924597?v=4 | A framework for few-shot evaluation of language models. | ['evaluation-framework', 'language-model', 'transformer'] | ['benchmark', 'evaluation', 'evaluation-framework', 'language-model', 'transformer'] | 2024-01-12 | [('ai21labs/lm-evaluation', 0.7471644282341003, 'llm', 2), ('huggingface/setfit', 0.6814461350440979, 'nlp', 0), ('freedomintelligence/llmzoo', 0.6675116419792175, 'llm', 1), ('openlmlab/leval', 0.6121481657028198, 'llm', 2), ('juncongmoo/pyllama', 0.6021994948387146, 'llm', 0), ('lm-sys/fastchat', 0.6016319394111633, ... | 103 | 2 | null | 29.67 | 484 | 372 | 41 | 0 | 1 | 1 | 1 | 484 | 1,016 | 90 | 2.1 | 57 |
486 | util | https://github.com/pydata/xarray | [] | null | [] | [] | null | null | null | pydata/xarray | xarray | 3,318 | 996 | 109 | Python | https://xarray.dev | N-D labeled arrays and datasets in Python | pydata | 2024-01-13 | 2013-09-30 | 539 | 6.154213 | https://avatars.githubusercontent.com/u/1284191?v=4 | N-D labeled arrays and datasets in Python | ['dask', 'netcdf', 'numpy', 'pandas', 'xarray'] | ['dask', 'netcdf', 'numpy', 'pandas', 'xarray'] | 2024-01-08 | [('holoviz/hvplot', 0.5328260064125061, 'pandas', 0), ('zarr-developers/zarr-python', 0.5044090151786804, 'data', 0)] | 465 | 6 | null | 9.1 | 425 | 283 | 125 | 0 | 15 | 9 | 15 | 425 | 1,167 | 90 | 2.7 | 57 |
1,298 | ml-ops | https://github.com/determined-ai/determined | [] | null | [] | [] | null | null | null | determined-ai/determined | determined | 2,696 | 338 | 75 | Go | https://determined.ai | Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow. | determined-ai | 2024-01-13 | 2020-04-07 | 199 | 13.547739 | https://avatars.githubusercontent.com/u/26636771?v=4 | Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow. | ['data-science', 'deep-learning', 'distributed-training', 'hyperparameter-optimization', 'hyperparameter-search', 'hyperparameter-tuning', 'keras', 'kubernetes', 'machine-learning', 'ml-infrastructure', 'ml-platform', 'mlops', 'pytorch', 'tensorflow'] | ['data-science', 'deep-learning', 'distributed-training', 'hyperparameter-optimization', 'hyperparameter-search', 'hyperparameter-tuning', 'keras', 'kubernetes', 'machine-learning', 'ml-infrastructure', 'ml-platform', 'mlops', 'pytorch', 'tensorflow'] | 2024-01-12 | [('tensorflow/tensorflow', 0.7361361384391785, 'ml-dl', 3), ('horovod/horovod', 0.6985735297203064, 'ml-ops', 5), ('microsoft/deepspeed', 0.6881573796272278, 'ml-dl', 3), ('mlflow/mlflow', 0.6798075437545776, 'ml-ops', 1), ('wandb/client', 0.6777682900428772, 'ml', 11), ('polyaxon/polyaxon', 0.6687636971473694, 'ml-ops... | 108 | 2 | null | 44.23 | 661 | 550 | 46 | 0 | 27 | 131 | 27 | 660 | 1,066 | 90 | 1.6 | 57 |
1,570 | llm | https://github.com/tairov/llama2.mojo | ['mojo'] | null | [] | [] | null | null | null | tairov/llama2.mojo | llama2.mojo | 1,773 | 111 | 23 | Python | https://www.modular.com/blog/community-spotlight-how-i-built-llama2-by-aydyn-tairov | Inference Llama 2 in one file of pure 🔥 | tairov | 2024-01-12 | 2023-09-10 | 20 | 87.401408 | null | Inference Llama 2 in one file of pure 🔥 | ['inference', 'llama', 'llama2', 'modular', 'mojo', 'parallelize', 'performance', 'simd', 'tensor', 'transformer-architecture', 'vectorization'] | ['inference', 'llama', 'llama2', 'modular', 'mojo', 'parallelize', 'performance', 'simd', 'tensor', 'transformer-architecture', 'vectorization'] | 2023-12-06 | [('karpathy/llama2.c', 0.8035979270935059, 'llm', 1), ('facebookresearch/llama', 0.7085148692131042, 'llm', 1), ('facebookresearch/llama-recipes', 0.6153814792633057, 'llm', 1), ('microsoft/llama-2-onnx', 0.6118836998939514, 'llm', 1), ('facebookresearch/codellama', 0.599827229976654, 'llm', 1), ('vllm-project/vllm', 0... | 12 | 4 | null | 1.98 | 31 | 16 | 4 | 1 | 0 | 0 | 0 | 31 | 83 | 90 | 2.7 | 57 |
430 | study | https://github.com/jakevdp/pythondatasciencehandbook | [] | null | [] | [] | null | null | null | jakevdp/pythondatasciencehandbook | PythonDataScienceHandbook | 40,567 | 17,512 | 1,772 | Jupyter Notebook | http://jakevdp.github.io/PythonDataScienceHandbook | Python Data Science Handbook: full text in Jupyter Notebooks | jakevdp | 2024-01-14 | 2016-08-10 | 389 | 104.056064 | null | Python Data Science Handbook: full text in Jupyter Notebooks | ['jupyter-notebook', 'matplotlib', 'numpy', 'pandas', 'scikit-learn'] | ['jupyter-notebook', 'matplotlib', 'numpy', 'pandas', 'scikit-learn'] | 2023-05-05 | [('wesm/pydata-book', 0.7202770709991455, 'study', 0), ('jupyter/nbformat', 0.6972000598907471, 'jupyter', 0), ('ageron/handson-ml2', 0.6813152432441711, 'ml', 0), ('tkrabel/bamboolib', 0.6585032939910889, 'pandas', 2), ('fchollet/deep-learning-with-python-notebooks', 0.6521231532096863, 'study', 0), ('mwaskom/seaborn'... | 17 | 7 | null | 0.02 | 8 | 1 | 90 | 8 | 0 | 0 | 0 | 8 | 3 | 90 | 0.4 | 56 |
128 | ml | https://github.com/microsoft/nni | [] | null | [] | [] | null | null | null | microsoft/nni | nni | 13,495 | 1,829 | 284 | Python | https://nni.readthedocs.io | An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. | microsoft | 2024-01-13 | 2018-06-01 | 295 | 45.657322 | https://avatars.githubusercontent.com/u/6154722?v=4 | An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. | ['automated-machine-learning', 'automl', 'bayesian-optimization', 'data-science', 'deep-learning', 'deep-neural-network', 'distributed', 'feature-engineering', 'hyperparameter-optimization', 'hyperparameter-tuning', 'machine-learning', 'machine-learning-algorithms', 'mlops', 'model-compression', 'nas', 'neural-architec... | ['automated-machine-learning', 'automl', 'bayesian-optimization', 'data-science', 'deep-learning', 'deep-neural-network', 'distributed', 'feature-engineering', 'hyperparameter-optimization', 'hyperparameter-tuning', 'machine-learning', 'machine-learning-algorithms', 'mlops', 'model-compression', 'nas', 'neural-architec... | 2023-10-26 | [('keras-team/autokeras', 0.8086925148963928, 'ml-dl', 6), ('microsoft/flaml', 0.7865293025970459, 'ml', 6), ('automl/auto-sklearn', 0.7624291777610779, 'ml', 5), ('awslabs/autogluon', 0.7000966668128967, 'ml', 7), ('nccr-itmo/fedot', 0.6999444365501404, 'ml-ops', 4), ('mlflow/mlflow', 0.6970524191856384, 'ml-ops', 1),... | 192 | 3 | null | 2.71 | 46 | 7 | 68 | 3 | 2 | 9 | 2 | 46 | 29 | 90 | 0.6 | 56 |
106 | nlp | https://github.com/nltk/nltk | [] | null | [] | [] | null | null | null | nltk/nltk | nltk | 12,688 | 2,824 | 468 | Python | https://www.nltk.org | NLTK Source | nltk | 2024-01-13 | 2009-09-07 | 751 | 16.891594 | https://avatars.githubusercontent.com/u/124114?v=4 | NLTK Source | ['machine-learning', 'natural-language-processing', 'nlp', 'nltk'] | ['machine-learning', 'natural-language-processing', 'nlp', 'nltk'] | 2023-12-24 | [('allenai/allennlp', 0.6935926675796509, 'nlp', 2), ('flairnlp/flair', 0.6725092530250549, 'nlp', 3), ('explosion/spacy-models', 0.6720556020736694, 'nlp', 3), ('explosion/spacy', 0.6628869771957397, 'nlp', 3), ('sloria/textblob', 0.6578431129455566, 'nlp', 3), ('lexpredict/lexpredict-lexnlp', 0.6562715172767639, 'nlp... | 452 | 6 | null | 1.58 | 82 | 46 | 175 | 1 | 0 | 3 | 3 | 82 | 125 | 90 | 1.5 | 56 |
1,336 | llm | https://github.com/blinkdl/rwkv-lm | [] | null | [] | [] | null | null | null | blinkdl/rwkv-lm | RWKV-LM | 10,652 | 753 | 129 | Python | null | RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding. | blinkdl | 2024-01-14 | 2021-08-08 | 129 | 82.39116 | null | RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding. | ['attention-mechanism', 'chatgpt', 'deep-learning', 'gpt', 'gpt-2', 'gpt-3', 'language-model', 'linear-attention', 'lstm', 'pytorch', 'rnn', 'rwkv', 'transformer', 'transformers'] | ['attention-mechanism', 'chatgpt', 'deep-learning', 'gpt', 'gpt-2', 'gpt-3', 'language-model', 'linear-attention', 'lstm', 'pytorch', 'rnn', 'rwkv', 'transformer', 'transformers'] | 2023-12-28 | [('blinkdl/chatrwkv', 0.6400032043457031, 'llm', 5), ('bytedance/lightseq', 0.5059091448783875, 'nlp', 2)] | 5 | 1 | null | 3.77 | 34 | 13 | 30 | 1 | 1 | 2 | 1 | 34 | 48 | 90 | 1.4 | 56 |
366 | ml | https://github.com/megvii-basedetection/yolox | [] | null | [] | [] | null | null | null | megvii-basedetection/yolox | YOLOX | 8,778 | 2,096 | 74 | Python | null | YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/ | megvii-basedetection | 2024-01-12 | 2021-07-17 | 132 | 66.28479 | https://avatars.githubusercontent.com/u/67775453?v=4 | YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/ | ['deep-learning', 'megengine', 'ncnn', 'object-detection', 'onnx', 'openvino', 'pytorch', 'tensorrt', 'yolo', 'yolov3', 'yolox'] | ['deep-learning', 'megengine', 'ncnn', 'object-detection', 'onnx', 'openvino', 'pytorch', 'tensorrt', 'yolo', 'yolov3', 'yolox'] | 2023-05-23 | [('microsoft/onnxruntime', 0.5817757844924927, 'ml', 3), ('deci-ai/super-gradients', 0.5785552859306335, 'ml-dl', 3), ('open-mmlab/mmdetection', 0.545394778251648, 'ml', 3), ('horovod/horovod', 0.5106202363967896, 'ml-ops', 2), ('neuralmagic/deepsparse', 0.5051378607749939, 'nlp', 2), ('roboflow/supervision', 0.5012127... | 74 | 5 | null | 0.15 | 49 | 13 | 30 | 8 | 0 | 2 | 2 | 49 | 46 | 90 | 0.9 | 56 |
456 | perf | https://github.com/nebuly-ai/nebullvm | [] | null | [] | [] | null | null | null | nebuly-ai/nebullvm | nebuly | 8,331 | 662 | 96 | Python | https://www.nebuly.com/ | The user analytics platform for LLMs | nebuly-ai | 2024-01-14 | 2022-02-12 | 102 | 81.334728 | https://avatars.githubusercontent.com/u/83510798?v=4 | The user analytics platform for LLMs | ['ai', 'analytics', 'artificial-intelligence', 'deeplearning', 'large-language-models', 'llm'] | ['ai', 'analytics', 'artificial-intelligence', 'deeplearning', 'large-language-models', 'llm'] | 2023-10-28 | [('pathwaycom/llm-app', 0.6677808165550232, 'llm', 1), ('microsoft/semantic-kernel', 0.6294217705726624, 'llm', 3), ('deepset-ai/haystack', 0.6285997033119202, 'llm', 2), ('tigerlab-ai/tiger', 0.6134838461875916, 'llm', 2), ('mlc-ai/mlc-llm', 0.6126720309257507, 'llm', 1), ('nomic-ai/gpt4all', 0.6061845421791077, 'llm'... | 40 | 5 | null | 8.1 | 0 | 0 | 23 | 3 | 5 | 13 | 5 | 0 | 0 | 90 | 0 | 56 |
1,034 | finance | https://github.com/quantconnect/lean | [] | null | [] | [] | null | null | null | quantconnect/lean | Lean | 8,317 | 3,085 | 415 | C# | https://lean.io | Lean Algorithmic Trading Engine by QuantConnect (Python, C#) | quantconnect | 2024-01-14 | 2014-11-28 | 478 | 17.378806 | https://avatars.githubusercontent.com/u/3912814?v=4 | Lean Algorithmic Trading Engine by QuantConnect (Python, C#) | ['algorithm', 'algorithmic-trading-engine', 'c-sharp', 'finance', 'forex', 'lean-engine', 'options', 'quantconnect', 'stock-indicators', 'trading', 'trading-algorithms', 'trading-bot', 'trading-platform', 'trading-strategies'] | ['algorithm', 'algorithmic-trading-engine', 'c-sharp', 'finance', 'forex', 'lean-engine', 'options', 'quantconnect', 'stock-indicators', 'trading', 'trading-algorithms', 'trading-bot', 'trading-platform', 'trading-strategies'] | 2024-01-11 | [('gbeced/pyalgotrade', 0.7084618806838989, 'finance', 0), ('quantopian/zipline', 0.6676159501075745, 'finance', 0), ('ranaroussi/quantstats', 0.6603469848632812, 'finance', 1), ('polakowo/vectorbt', 0.6572080254554749, 'finance', 3), ('goldmansachs/gs-quant', 0.6400971412658691, 'finance', 1), ('zvtvz/zvt', 0.63760459... | 198 | 2 | null | 10.94 | 236 | 170 | 111 | 0 | 0 | 331 | 331 | 236 | 127 | 90 | 0.5 | 56 |
420 | ml-dl | https://github.com/pyro-ppl/pyro | [] | null | [] | [] | null | null | null | pyro-ppl/pyro | pyro | 8,243 | 985 | 204 | Python | http://pyro.ai | Deep universal probabilistic programming with Python and PyTorch | pyro-ppl | 2024-01-13 | 2017-06-16 | 345 | 23.853245 | https://avatars.githubusercontent.com/u/46794900?v=4 | Deep universal probabilistic programming with Python and PyTorch | ['bayesian', 'bayesian-inference', 'deep-learning', 'machine-learning', 'probabilistic-modeling', 'probabilistic-programming', 'pytorch', 'variational-inference'] | ['bayesian', 'bayesian-inference', 'deep-learning', 'machine-learning', 'probabilistic-modeling', 'probabilistic-programming', 'pytorch', 'variational-inference'] | 2024-01-14 | [('pymc-devs/pymc3', 0.6964523792266846, 'ml', 3), ('intellabs/bayesian-torch', 0.6956607699394226, 'ml', 3), ('probml/pyprobml', 0.6461431980133057, 'ml', 3), ('pytorch/botorch', 0.6212801933288574, 'ml-dl', 0), ('thu-ml/tianshou', 0.5777061581611633, 'ml-rl', 1), ('huggingface/transformers', 0.5731987953186035, 'nlp'... | 148 | 5 | null | 1.27 | 39 | 26 | 80 | 0 | 2 | 5 | 2 | 39 | 51 | 90 | 1.3 | 56 |
1,260 | llm | https://github.com/microsoft/lora | [] | null | [] | [] | null | null | null | microsoft/lora | LoRA | 7,851 | 476 | 58 | Python | https://arxiv.org/abs/2106.09685 | Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models" | microsoft | 2024-01-14 | 2021-06-18 | 136 | 57.486402 | https://avatars.githubusercontent.com/u/6154722?v=4 | Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models" | ['adaptation', 'deberta', 'deep-learning', 'gpt-2', 'gpt-3', 'language-model', 'lora', 'low-rank', 'pytorch', 'roberta'] | ['adaptation', 'deberta', 'deep-learning', 'gpt-2', 'gpt-3', 'language-model', 'lora', 'low-rank', 'pytorch', 'roberta'] | 2024-01-09 | [('hannibal046/awesome-llm', 0.6244948506355286, 'study', 1), ('next-gpt/next-gpt', 0.6170973181724548, 'llm', 0), ('lianjiatech/belle', 0.5939985513687134, 'llm', 1), ('bobazooba/xllm', 0.5789094567298889, 'llm', 2), ('microsoft/autogen', 0.5736963152885437, 'llm', 0), ('hiyouga/llama-efficient-tuning', 0.573307514190... | 12 | 3 | null | 0.37 | 26 | 7 | 31 | 0 | 0 | 2 | 2 | 26 | 31 | 90 | 1.2 | 56 |
469 | gui | https://github.com/parthjadhav/tkinter-designer | [] | null | [] | [] | null | null | null | parthjadhav/tkinter-designer | Tkinter-Designer | 7,773 | 742 | 78 | Python | null | An easy and fast way to create a Python GUI 🐍 | parthjadhav | 2024-01-14 | 2021-05-18 | 141 | 55.12766 | null | An easy and fast way to create a Python GUI 🐍 | ['automatic', 'collaborate', 'drag-and-drop', 'easy', 'easy-to-use', 'fast', 'figma', 'gui', 'gui-application', 'learn', 'python-script', 'tkinter', 'tkinter-designer', 'tkinter-graphic-interface', 'tkinter-gui', 'tkinter-python', 'tkinter-widgets'] | ['automatic', 'collaborate', 'drag-and-drop', 'easy', 'easy-to-use', 'fast', 'figma', 'gui', 'gui-application', 'learn', 'python-script', 'tkinter', 'tkinter-designer', 'tkinter-graphic-interface', 'tkinter-gui', 'tkinter-python', 'tkinter-widgets'] | 2024-01-04 | [('pysimplegui/pysimplegui', 0.7242632508277893, 'gui', 4), ('hoffstadt/dearpygui', 0.6940200924873352, 'gui', 1), ('r0x0r/pywebview', 0.6899272799491882, 'gui', 1), ('beeware/toga', 0.6891065239906311, 'gui', 1), ('willmcgugan/textual', 0.5848771333694458, 'term', 0), ('wxwidgets/phoenix', 0.58327716588974, 'gui', 1),... | 45 | 2 | null | 0.23 | 39 | 10 | 32 | 0 | 1 | 3 | 1 | 39 | 59 | 90 | 1.5 | 56 |
923 | ml-rl | https://github.com/lucidrains/palm-rlhf-pytorch | [] | null | [] | [] | null | null | null | lucidrains/palm-rlhf-pytorch | PaLM-rlhf-pytorch | 7,494 | 649 | 139 | Python | null | Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM | lucidrains | 2024-01-12 | 2022-12-09 | 59 | 125.798561 | null | Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM | ['artificial-intelligence', 'attention-mechanisms', 'deep-learning', 'human-feedback', 'reinforcement-learning', 'transformers'] | ['artificial-intelligence', 'attention-mechanisms', 'deep-learning', 'human-feedback', 'reinforcement-learning', 'transformers'] | 2023-04-05 | [('denys88/rl_games', 0.5653679370880127, 'ml-rl', 2), ('deepmind/android_env', 0.5164604187011719, 'ml-dl', 1)] | 5 | 3 | null | 0.58 | 4 | 2 | 13 | 9 | 15 | 65 | 15 | 4 | 4 | 90 | 1 | 56 |
960 | ml-rl | https://github.com/thu-ml/tianshou | [] | null | [] | [] | null | null | null | thu-ml/tianshou | tianshou | 7,086 | 1,071 | 90 | Python | https://tianshou.readthedocs.io | An elegant PyTorch deep reinforcement learning library. | thu-ml | 2024-01-12 | 2018-04-16 | 302 | 23.452482 | https://avatars.githubusercontent.com/u/19198992?v=4 | An elegant PyTorch deep reinforcement learning library. | ['a2c', 'atari', 'bcq', 'benchmark', 'cql', 'ddpg', 'double-dqn', 'dqn', 'drl', 'imitation-learning', 'mujoco', 'npg', 'policy-gradient', 'ppo', 'pytorch', 'rl', 'sac', 'td3', 'trpo'] | ['a2c', 'atari', 'bcq', 'benchmark', 'cql', 'ddpg', 'double-dqn', 'dqn', 'drl', 'imitation-learning', 'mujoco', 'npg', 'policy-gradient', 'ppo', 'pytorch', 'rl', 'sac', 'td3', 'trpo'] | 2024-01-12 | [('denys88/rl_games', 0.7549825310707092, 'ml-rl', 1), ('pytorch/rl', 0.7527033090591431, 'ml-rl', 2), ('humancompatibleai/imitation', 0.7333576679229736, 'ml-rl', 1), ('openai/baselines', 0.6823237538337708, 'ml-rl', 0), ('salesforce/warp-drive', 0.6808977723121643, 'ml-rl', 1), ('tensorlayer/tensorlayer', 0.660316407... | 65 | 4 | null | 4.12 | 77 | 37 | 70 | 0 | 1 | 5 | 1 | 77 | 155 | 90 | 2 | 56 |
717 | ml | https://github.com/py-why/dowhy | [] | null | [] | [] | null | null | null | py-why/dowhy | dowhy | 6,454 | 883 | 137 | Python | https://www.pywhy.org/dowhy | DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks. | py-why | 2024-01-13 | 2018-05-31 | 295 | 21.825121 | https://avatars.githubusercontent.com/u/101266056?v=4 | DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks. | ['bayesian-networks', 'causal-inference', 'causal-machine-learning', 'causal-models', 'causality', 'data-science', 'do-calculus', 'graphical-models', 'machine-learning', 'treatment-effects'] | ['bayesian-networks', 'causal-inference', 'causal-machine-learning', 'causal-models', 'causality', 'data-science', 'do-calculus', 'graphical-models', 'machine-learning', 'treatment-effects'] | 2024-01-08 | [('mckinsey/causalnex', 0.7358757853507996, 'math', 5), ('willianfuks/tfcausalimpact', 0.6020914912223816, 'math', 1), ('py-why/econml', 0.5789477229118347, 'ml', 4), ('eleutherai/pyfra', 0.5379133820533752, 'ml', 0), ('quantecon/quantecon.py', 0.513481080532074, 'sim', 0)] | 82 | 5 | null | 3.46 | 119 | 107 | 68 | 0 | 4 | 3 | 4 | 119 | 102 | 90 | 0.9 | 56 |
278 | jupyter | https://github.com/nteract/papermill | [] | null | [] | [] | null | null | null | nteract/papermill | papermill | 5,497 | 409 | 93 | Python | http://papermill.readthedocs.io/en/latest/ | 📚 Parameterize, execute, and analyze notebooks | nteract | 2024-01-14 | 2017-07-06 | 342 | 16.0396 | https://avatars.githubusercontent.com/u/12401040?v=4 | 📚 Parameterize, execute, and analyze notebooks | ['julia', 'jupyter', 'notebook', 'notebook-generator', 'notebooks', 'nteract', 'pipeline', 'publishing', 'r', 'scala'] | ['julia', 'jupyter', 'notebook', 'notebook-generator', 'notebooks', 'nteract', 'pipeline', 'publishing', 'r', 'scala'] | 2024-01-01 | [('mwouts/jupytext', 0.632023811340332, 'jupyter', 1), ('jupyter/nbformat', 0.618989109992981, 'jupyter', 0), ('cohere-ai/notebooks', 0.5747708082199097, 'llm', 1), ('jupyter/notebook', 0.5524148344993591, 'jupyter', 2), ('aws/graph-notebook', 0.5402319431304932, 'jupyter', 1), ('linealabs/lineapy', 0.5371261835098267,... | 114 | 7 | null | 0.69 | 51 | 40 | 79 | 0 | 0 | 12 | 12 | 51 | 86 | 90 | 1.7 | 56 |
361 | ml-ops | https://github.com/allegroai/clearml | [] | null | [] | [] | null | null | null | allegroai/clearml | clearml | 4,979 | 626 | 91 | Python | https://clear.ml/docs | ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management | allegroai | 2024-01-14 | 2019-06-10 | 242 | 20.562242 | https://avatars.githubusercontent.com/u/38647316?v=4 | ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management | ['ai', 'clearml', 'control', 'deep-learning', 'deeplearning', 'devops', 'experiment', 'experiment-manager', 'k8s', 'machine-learning', 'machinelearning', 'mlops', 'trains', 'trainsai', 'version', 'version-control'] | ['ai', 'clearml', 'control', 'deep-learning', 'deeplearning', 'devops', 'experiment', 'experiment-manager', 'k8s', 'machine-learning', 'machinelearning', 'mlops', 'trains', 'trainsai', 'version', 'version-control'] | 2024-01-12 | [('zenml-io/zenml', 0.66759192943573, 'ml-ops', 4), ('polyaxon/polyaxon', 0.6574744582176208, 'ml-ops', 4), ('iterative/dvc', 0.618588924407959, 'ml-ops', 2), ('bodywork-ml/bodywork-core', 0.6049355268478394, 'ml-ops', 3), ('netflix/metaflow', 0.5861303210258484, 'ml-ops', 3), ('fmind/mlops-python-package', 0.583376884... | 88 | 3 | null | 2.83 | 74 | 21 | 56 | 0 | 18 | 34 | 18 | 74 | 141 | 90 | 1.9 | 56 |
1,371 | llm | https://github.com/minedojo/voyager | [] | null | [] | [] | null | null | null | minedojo/voyager | Voyager | 4,708 | 445 | 60 | JavaScript | https://voyager.minedojo.org/ | An Open-Ended Embodied Agent with Large Language Models | minedojo | 2024-01-14 | 2023-05-25 | 35 | 131.824 | https://avatars.githubusercontent.com/u/98871221?v=4 | An Open-Ended Embodied Agent with Large Language Models | ['embodied-learning', 'large-language-models', 'minecraft', 'open-ended-learning'] | ['embodied-learning', 'large-language-models', 'minecraft', 'open-ended-learning'] | 2023-07-27 | [('facebookresearch/droidlet', 0.6723781228065491, 'sim', 0), ('facebookresearch/habitat-lab', 0.6467283964157104, 'sim', 0), ('aiwaves-cn/agents', 0.5751522183418274, 'nlp', 0), ('jina-ai/thinkgpt', 0.5710037350654602, 'llm', 0), ('humanoidagents/humanoidagents', 0.56615149974823, 'sim', 0), ('lm-sys/fastchat', 0.5574... | 13 | 4 | null | 0.42 | 23 | 16 | 8 | 6 | 0 | 0 | 0 | 23 | 25 | 90 | 1.1 | 56 |
375 | util | https://github.com/spotify/pedalboard | [] | null | [] | [] | null | null | null | spotify/pedalboard | pedalboard | 4,677 | 219 | 56 | C++ | https://spotify.github.io/pedalboard/ | 🎛 🔊 A Python library for working with audio. | spotify | 2024-01-13 | 2021-07-06 | 134 | 34.902985 | https://avatars.githubusercontent.com/u/251374?v=4 | 🎛 🔊 A Python library for working with audio. | ['audio', 'audio-processing', 'audio-production', 'audio-research', 'audio-unit', 'juce', 'pybind11', 'tensorflow', 'vst3', 'vst3-host'] | ['audio', 'audio-processing', 'audio-production', 'audio-research', 'audio-unit', 'juce', 'pybind11', 'tensorflow', 'vst3', 'vst3-host'] | 2023-12-14 | [('bastibe/python-soundfile', 0.7314440608024597, 'util', 0), ('irmen/pyminiaudio', 0.7280553579330444, 'util', 0), ('uberi/speech_recognition', 0.6759282946586609, 'ml', 1), ('taylorsmarks/playsound', 0.6269357204437256, 'util', 0), ('libaudioflux/audioflux', 0.5974409580230713, 'util', 2), ('speechbrain/speechbrain',... | 27 | 5 | null | 2.19 | 35 | 13 | 31 | 1 | 20 | 22 | 20 | 35 | 42 | 90 | 1.2 | 56 |
1,452 | util | https://github.com/conda-forge/miniforge | [] | null | [] | [] | null | null | null | conda-forge/miniforge | miniforge | 4,654 | 266 | 50 | Shell | https://conda-forge.org/miniforge | A conda-forge distribution. | conda-forge | 2024-01-14 | 2019-11-14 | 219 | 21.182055 | https://avatars.githubusercontent.com/u/11897326?v=4 | A conda-forge distribution. | [] | [] | 2023-12-21 | [('conda/conda-pack', 0.5824256539344788, 'util', 0), ('mamba-org/quetz', 0.5642527341842651, 'util', 0), ('conda-forge/feedstocks', 0.5309390425682068, 'util', 0), ('mamba-org/boa', 0.5230752825737, 'util', 0)] | 37 | 5 | null | 1.42 | 59 | 30 | 51 | 1 | 15 | 19 | 15 | 59 | 143 | 90 | 2.4 | 56 |
347 | ml-ops | https://github.com/evidentlyai/evidently | [] | null | [] | [] | null | null | null | evidentlyai/evidently | evidently | 4,312 | 477 | 43 | Jupyter Notebook | null | Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b | evidentlyai | 2024-01-12 | 2020-11-25 | 165 | 25.998277 | https://avatars.githubusercontent.com/u/75031056?v=4 | Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b | ['data-drift', 'data-science', 'html-report', 'jupyter-notebook', 'machine-learning', 'machine-learning-operations', 'mlops', 'model-monitoring', 'pandas-dataframe', 'production-machine-learning'] | ['data-drift', 'data-science', 'html-report', 'jupyter-notebook', 'machine-learning', 'machine-learning-operations', 'mlops', 'model-monitoring', 'pandas-dataframe', 'production-machine-learning'] | 2024-01-12 | [('deepchecks/deepchecks', 0.6157994866371155, 'data', 8), ('fmind/mlops-python-package', 0.5556315779685974, 'template', 1), ('selfexplainml/piml-toolbox', 0.5544941425323486, 'ml-interpretability', 0), ('huggingface/evaluate', 0.5467391014099121, 'ml', 1), ('kubeflow/fairing', 0.531782329082489, 'ml-ops', 0), ('distr... | 57 | 3 | null | 6.9 | 148 | 121 | 38 | 0 | 25 | 21 | 25 | 148 | 76 | 90 | 0.5 | 56 |
826 | util | https://github.com/adafruit/circuitpython | [] | null | [] | [] | null | null | null | adafruit/circuitpython | circuitpython | 3,787 | 1,073 | 128 | C | https://circuitpython.org | CircuitPython - a Python implementation for teaching coding with microcontrollers | adafruit | 2024-01-13 | 2016-08-20 | 388 | 9.74954 | https://avatars.githubusercontent.com/u/181069?v=4 | CircuitPython - a Python implementation for teaching coding with microcontrollers | ['beginner', 'circuitpython', 'cpython', 'education', 'embedded', 'microcontroller', 'micropython'] | ['beginner', 'circuitpython', 'cpython', 'education', 'embedded', 'microcontroller', 'micropython'] | 2024-01-13 | [('micropython/micropython', 0.7091054916381836, 'util', 3), ('python/cpython', 0.6647933125495911, 'util', 1), ('fchollet/deep-learning-with-python-notebooks', 0.6453861594200134, 'study', 0), ('pypy/pypy', 0.6234596371650696, 'util', 1), ('pyston/pyston', 0.5873665809631348, 'util', 0), ('norvig/pytudes', 0.572238087... | 1,121 | 4 | null | 0 | 538 | 356 | 90 | 0 | 30 | 37 | 30 | 537 | 1,228 | 90 | 2.3 | 56 |
918 | study | https://github.com/roboflow/notebooks | [] | null | [] | [] | null | null | null | roboflow/notebooks | notebooks | 3,584 | 553 | 54 | Jupyter Notebook | https://roboflow.com/models | Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM. | roboflow | 2024-01-13 | 2022-11-18 | 62 | 57.278539 | https://avatars.githubusercontent.com/u/53104118?v=4 | Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM. | ['amazon-sagemaker-lab', 'automatic-labeling-system', 'computer-vision', 'deep-learning', 'deep-neural-networks', 'google-colab', 'image-classification', 'image-segmentation', 'machine-learning', 'object-detection', 'open-vocabulary-detection', 'open-vocabulary-segmentation', 'pytorch', 'tutorial', 'yolov5', 'yolov6', ... | ['amazon-sagemaker-lab', 'automatic-labeling-system', 'computer-vision', 'deep-learning', 'deep-neural-networks', 'google-colab', 'image-classification', 'image-segmentation', 'machine-learning', 'object-detection', 'open-vocabulary-detection', 'open-vocabulary-segmentation', 'pytorch', 'tutorial', 'yolov5', 'yolov6', ... | 2024-01-10 | [('deci-ai/super-gradients', 0.8082399368286133, 'ml-dl', 5), ('roboflow/supervision', 0.6496574878692627, 'ml', 5), ('lucidrains/vit-pytorch', 0.6355553865432739, 'ml-dl', 2), ('idea-research/grounded-segment-anything', 0.6104524731636047, 'llm', 3), ('google-research/maxvit', 0.5931783318519592, 'ml', 2), ('facebookr... | 21 | 3 | null | 2.79 | 33 | 16 | 14 | 0 | 0 | 1 | 1 | 32 | 33 | 90 | 1 | 56 |
878 | study | https://github.com/huggingface/deep-rl-class | [] | null | [] | [] | null | null | null | huggingface/deep-rl-class | deep-rl-class | 3,426 | 510 | 86 | MDX | null | This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course. | huggingface | 2024-01-13 | 2022-04-21 | 92 | 36.952234 | https://avatars.githubusercontent.com/u/25720743?v=4 | This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course. | ['deep-learning', 'deep-reinforcement-learning', 'reinforcement-learning', 'reinforcement-learning-excercises'] | ['deep-learning', 'deep-reinforcement-learning', 'reinforcement-learning', 'reinforcement-learning-excercises'] | 2024-01-02 | [('openai/spinningup', 0.5750541090965271, 'study', 0), ('huggingface/huggingface_hub', 0.5541204810142517, 'ml', 1), ('huggingface/diffusion-models-class', 0.551882803440094, 'study', 0), ('tensorlayer/tensorlayer', 0.5484325885772705, 'ml-rl', 2), ('farama-foundation/gymnasium', 0.5383160710334778, 'ml-rl', 1), ('nvi... | 86 | 3 | null | 6.08 | 64 | 37 | 21 | 0 | 0 | 0 | 0 | 64 | 122 | 90 | 1.9 | 56 |
362 | ml-ops | https://github.com/kubeflow/pipelines | [] | null | [] | [] | null | null | null | kubeflow/pipelines | pipelines | 3,364 | 1,513 | 104 | Python | https://www.kubeflow.org/docs/components/pipelines/ | Machine Learning Pipelines for Kubeflow | kubeflow | 2024-01-13 | 2018-05-12 | 298 | 11.272379 | https://avatars.githubusercontent.com/u/33164907?v=4 | Machine Learning Pipelines for Kubeflow | ['data-science', 'kubeflow', 'kubeflow-pipelines', 'kubernetes', 'machine-learning', 'mlops', 'pipeline'] | ['data-science', 'kubeflow', 'kubeflow-pipelines', 'kubernetes', 'machine-learning', 'mlops', 'pipeline'] | 2024-01-12 | [('bodywork-ml/bodywork-core', 0.8104010820388794, 'ml-ops', 5), ('getindata/kedro-kubeflow', 0.7283107042312622, 'ml-ops', 3), ('polyaxon/polyaxon', 0.7241019010543823, 'ml-ops', 4), ('kubeflow-kale/kale', 0.692866325378418, 'ml-ops', 3), ('orchest/orchest', 0.6418040990829468, 'ml-ops', 3), ('feast-dev/feast', 0.6390... | 386 | 1 | null | 18.08 | 597 | 336 | 69 | 0 | 31 | 28 | 31 | 596 | 1,212 | 90 | 2 | 56 |
728 | data | https://github.com/ibis-project/ibis | [] | null | [] | [] | 1 | null | null | ibis-project/ibis | ibis | 3,364 | 466 | 80 | Python | https://ibis-project.org | The flexibility of Python with the scale and performance of modern SQL. | ibis-project | 2024-01-14 | 2015-04-17 | 458 | 7.335826 | https://avatars.githubusercontent.com/u/27442526?v=4 | The flexibility of Python with the scale and performance of modern SQL. | ['bigquery', 'clickhouse', 'dask', 'database', 'datafusion', 'duckdb', 'impala', 'mssql', 'mysql', 'pandas', 'polars', 'postgresql', 'pyarrow', 'pyspark', 'snowflake', 'sql', 'sqlalchemy', 'sqlite', 'trino'] | ['bigquery', 'clickhouse', 'dask', 'database', 'datafusion', 'duckdb', 'impala', 'mssql', 'mysql', 'pandas', 'polars', 'postgresql', 'pyarrow', 'pyspark', 'snowflake', 'sql', 'sqlalchemy', 'sqlite', 'trino'] | 2024-01-13 | [('tiangolo/sqlmodel', 0.8095237612724304, 'data', 2), ('tobymao/sqlglot', 0.7856696248054504, 'data', 8), ('sqlalchemy/sqlalchemy', 0.741746723651886, 'data', 2), ('kayak/pypika', 0.6313249468803406, 'data', 1), ('machow/siuba', 0.6308576464653015, 'pandas', 2), ('mcfunley/pugsql', 0.6264197826385498, 'data', 1), ('ma... | 165 | 4 | null | 55.63 | 674 | 586 | 106 | 0 | 9 | 5 | 9 | 673 | 1,004 | 90 | 1.5 | 56 |
870 | time-series | https://github.com/nixtla/statsforecast | [] | null | [] | [] | null | null | null | nixtla/statsforecast | statsforecast | 3,316 | 223 | 31 | Python | https://nixtlaverse.nixtla.io/statsforecast | Lightning ⚡️ fast forecasting with statistical and econometric models. | nixtla | 2024-01-14 | 2021-11-24 | 113 | 29.124216 | https://avatars.githubusercontent.com/u/79945230?v=4 | Lightning ⚡️ fast forecasting with statistical and econometric models. | ['arima', 'automl', 'baselines', 'data-science', 'econometrics', 'ets', 'exponential-smoothing', 'fbprophet', 'forecasting', 'machine-learning', 'mstl', 'naive', 'neuralprophet', 'predictions', 'prophet', 'seasonal-naive', 'statistics', 'theta', 'time-series'] | ['arima', 'automl', 'baselines', 'data-science', 'econometrics', 'ets', 'exponential-smoothing', 'fbprophet', 'forecasting', 'machine-learning', 'mstl', 'naive', 'neuralprophet', 'predictions', 'prophet', 'seasonal-naive', 'statistics', 'theta', 'time-series'] | 2024-01-12 | [('ourownstory/neural_prophet', 0.6677179336547852, 'ml', 6), ('winedarksea/autots', 0.6360719799995422, 'time-series', 4), ('linkedin/greykite', 0.5983828902244568, 'ml', 0), ('facebook/prophet', 0.586733341217041, 'time-series', 2), ('alkaline-ml/pmdarima', 0.5763822197914124, 'time-series', 5), ('firmai/atspy', 0.57... | 35 | 3 | null | 3.21 | 126 | 102 | 26 | 0 | 4 | 14 | 4 | 126 | 183 | 90 | 1.5 | 56 |
595 | gis | https://github.com/giswqs/geemap | [] | null | [] | [] | null | null | null | giswqs/geemap | geemap | 3,049 | 1,042 | 116 | Python | https://geemap.org | A Python package for interactive geospaital analysis and visualization with Google Earth Engine. | giswqs | 2024-01-14 | 2020-03-08 | 203 | 14.998595 | https://avatars.githubusercontent.com/u/26841718?v=4 | A Python package for interactive geospaital analysis and visualization with Google Earth Engine. | ['colab', 'data-science', 'dataviz', 'earth-engine', 'earthengine', 'folium', 'geospatial', 'gis', 'google-earth-engine', 'image-processing', 'ipyleaflet', 'ipywidgets', 'jupyter', 'jupyter-notebook', 'landsat', 'mapping', 'remote-sensing', 'streamlit', 'streamlit-webapp'] | ['colab', 'data-science', 'dataviz', 'earth-engine', 'earthengine', 'folium', 'geospatial', 'gis', 'google-earth-engine', 'image-processing', 'ipyleaflet', 'ipywidgets', 'jupyter', 'jupyter-notebook', 'landsat', 'mapping', 'remote-sensing', 'streamlit', 'streamlit-webapp'] | 2024-01-12 | [('opengeos/leafmap', 0.7121515274047852, 'gis', 11), ('scitools/iris', 0.6783716082572937, 'gis', 0), ('residentmario/geoplot', 0.6778126358985901, 'gis', 0), ('raphaelquast/eomaps', 0.6554696559906006, 'gis', 3), ('holoviz/holoviz', 0.6438645124435425, 'viz', 0), ('bokeh/bokeh', 0.6420087218284607, 'viz', 1), ('holov... | 52 | 5 | null | 5.27 | 83 | 79 | 47 | 0 | 45 | 46 | 45 | 83 | 168 | 90 | 2 | 56 |
549 | ml-dl | https://github.com/pytorch/botorch | [] | null | [] | [] | null | null | null | pytorch/botorch | botorch | 2,871 | 359 | 53 | Jupyter Notebook | https://botorch.org/ | Bayesian optimization in PyTorch | pytorch | 2024-01-14 | 2018-07-30 | 287 | 9.998507 | https://avatars.githubusercontent.com/u/21003710?v=4 | Bayesian optimization in PyTorch | [] | [] | 2024-01-12 | [('pyro-ppl/pyro', 0.6212801933288574, 'ml-dl', 0), ('intellabs/bayesian-torch', 0.6108170747756958, 'ml', 0), ('bayesianmodelingandcomputationinpython/bookcode_edition1', 0.5796522498130798, 'study', 0), ('pytorch/ignite', 0.5717622637748718, 'ml-dl', 0), ('nvidia/apex', 0.5640817880630493, 'ml-dl', 0), ('laekov/fastm... | 108 | 4 | null | 6.67 | 131 | 111 | 66 | 0 | 10 | 8 | 10 | 131 | 512 | 90 | 3.9 | 56 |
436 | gis | https://github.com/opengeos/leafmap | [] | null | [] | [] | null | null | null | opengeos/leafmap | leafmap | 2,809 | 326 | 52 | Python | https://leafmap.org | A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment | opengeos | 2024-01-13 | 2021-03-10 | 150 | 18.620265 | https://avatars.githubusercontent.com/u/129896036?v=4 | A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment | ['data-science', 'dataviz', 'folium', 'geoparquet', 'geopython', 'geospatial', 'geospatial-analysis', 'gis', 'ipyleaflet', 'jupyter', 'jupyter-notebook', 'leafmap', 'mapping', 'plotly', 'streamlit', 'streamlit-webapp', 'whiteboxtools'] | ['data-science', 'dataviz', 'folium', 'geoparquet', 'geopython', 'geospatial', 'geospatial-analysis', 'gis', 'ipyleaflet', 'jupyter', 'jupyter-notebook', 'leafmap', 'mapping', 'plotly', 'streamlit', 'streamlit-webapp', 'whiteboxtools'] | 2024-01-11 | [('giswqs/geemap', 0.7121515274047852, 'gis', 11), ('residentmario/geoplot', 0.6929628252983093, 'gis', 0), ('raphaelquast/eomaps', 0.6778762936592102, 'gis', 3), ('geopandas/geopandas', 0.671466052532196, 'gis', 3), ('vizzuhq/ipyvizzu', 0.6331526637077332, 'jupyter', 3), ('holoviz/panel', 0.6154477596282959, 'viz', 3)... | 29 | 6 | null | 5.35 | 77 | 74 | 35 | 0 | 58 | 43 | 58 | 77 | 104 | 90 | 1.4 | 56 |
806 | data | https://github.com/datafold/data-diff | [] | null | [] | [] | null | null | null | datafold/data-diff | data-diff | 2,686 | 189 | 21 | Python | https://docs.datafold.com | Compare tables within or across databases | datafold | 2024-01-14 | 2022-03-07 | 99 | 27.092219 | https://avatars.githubusercontent.com/u/63129412?v=4 | Compare tables within or across databases | ['data', 'data-diffing', 'data-engineering', 'data-quality', 'data-quality-monitoring', 'data-science', 'database', 'databricks-sql', 'dataengineering', 'dataquality', 'dbt', 'mysql', 'oracle-database', 'postgres', 'postgresql', 'rdbms', 'snowflake', 'sql', 'trino'] | ['data', 'data-diffing', 'data-engineering', 'data-quality', 'data-quality-monitoring', 'data-science', 'database', 'databricks-sql', 'dataengineering', 'dataquality', 'dbt', 'mysql', 'oracle-database', 'postgres', 'postgresql', 'rdbms', 'snowflake', 'sql', 'trino'] | 2024-01-12 | [('ibis-project/ibis', 0.5967792272567749, 'data', 6), ('tobymao/sqlglot', 0.5574495196342468, 'data', 5), ('tiangolo/sqlmodel', 0.5563005805015564, 'data', 1), ('dbt-labs/dbt-core', 0.550411581993103, 'ml-ops', 0), ('great-expectations/great_expectations', 0.5429127216339111, 'ml-ops', 4), ('unionai-oss/pandera', 0.53... | 53 | 2 | null | 11.88 | 133 | 98 | 23 | 0 | 48 | 32 | 48 | 133 | 120 | 90 | 0.9 | 56 |
1,628 | llm | https://github.com/next-gpt/next-gpt | [] | null | [] | [] | null | null | null | next-gpt/next-gpt | NExT-GPT | 2,579 | 266 | 57 | Python | https://next-gpt.github.io/ | Code and models for NExT-GPT: Any-to-Any Multimodal Large Language Model | next-gpt | 2024-01-13 | 2023-08-30 | 21 | 117.993464 | null | Code and models for NExT-GPT: Any-to-Any Multimodal Large Language Model | ['chatgpt', 'foundation-models', 'gpt-4', 'instruction-tuning', 'large-language-models', 'llm', 'multi-modal-chatgpt', 'multimodal', 'visual-language-learning'] | ['chatgpt', 'foundation-models', 'gpt-4', 'instruction-tuning', 'large-language-models', 'llm', 'multi-modal-chatgpt', 'multimodal', 'visual-language-learning'] | 2024-01-09 | [('microsoft/autogen', 0.7022780776023865, 'llm', 2), ('hannibal046/awesome-llm', 0.6860809922218323, 'study', 0), ('lianjiatech/belle', 0.6763371229171753, 'llm', 0), ('mlc-ai/web-llm', 0.6524577140808105, 'llm', 2), ('xtekky/gpt4free', 0.6495850086212158, 'llm', 2), ('guidance-ai/guidance', 0.6470729112625122, 'llm',... | 4 | 2 | null | 4.06 | 58 | 21 | 5 | 0 | 0 | 0 | 0 | 58 | 30 | 90 | 0.5 | 56 |
835 | ml | https://github.com/aws/sagemaker-python-sdk | [] | null | [] | [] | null | null | null | aws/sagemaker-python-sdk | sagemaker-python-sdk | 1,995 | 1,104 | 132 | Python | https://sagemaker.readthedocs.io/ | A library for training and deploying machine learning models on Amazon SageMaker | aws | 2024-01-12 | 2017-11-14 | 324 | 6.157407 | https://avatars.githubusercontent.com/u/2232217?v=4 | A library for training and deploying machine learning models on Amazon SageMaker | ['aws', 'huggingface', 'machine-learning', 'mxnet', 'pytorch', 'sagemaker', 'tensorflow'] | ['aws', 'huggingface', 'machine-learning', 'mxnet', 'pytorch', 'sagemaker', 'tensorflow'] | 2024-01-11 | [('aws-samples/sagemaker-ssh-helper', 0.671806812286377, 'util', 3), ('huggingface/huggingface_hub', 0.6623826026916504, 'ml', 2), ('mlflow/mlflow', 0.6176590919494629, 'ml-ops', 1), ('ashleve/lightning-hydra-template', 0.6082078814506531, 'util', 1), ('kubeflow/fairing', 0.5987374186515808, 'ml-ops', 0), ('merantix-mo... | 417 | 2 | null | 12.08 | 465 | 368 | 75 | 0 | 88 | 91 | 88 | 465 | 2,810 | 90 | 6 | 56 |
1,242 | ml-interpretability | https://github.com/arize-ai/phoenix | [] | null | [] | [] | null | null | null | arize-ai/phoenix | phoenix | 1,906 | 128 | 23 | Jupyter Notebook | https://docs.arize.com/phoenix | AI Observability & Evaluation - Evaluate, troubleshoot, and fine tune your LLM, CV, and NLP models in a notebook. | arize-ai | 2024-01-13 | 2022-11-09 | 63 | 29.847875 | https://avatars.githubusercontent.com/u/59858760?v=4 | AI Observability & Evaluation - Evaluate, troubleshoot, and fine tune your LLM, CV, and NLP models in a notebook. | ['ai-monitoring', 'ai-observability', 'ai-roi', 'clustering', 'llm-eval', 'llmops', 'ml-monitoring', 'ml-observability', 'mlops', 'model-monitoring', 'model-observability', 'umap'] | ['ai-monitoring', 'ai-observability', 'ai-roi', 'clustering', 'llm-eval', 'llmops', 'ml-monitoring', 'ml-observability', 'mlops', 'model-monitoring', 'model-observability', 'umap'] | 2024-01-12 | [('giskard-ai/giskard', 0.6145030856132507, 'data', 2), ('microsoft/lmops', 0.5890821814537048, 'llm', 0), ('llmware-ai/llmware', 0.5607779026031494, 'llm', 0), ('bentoml/bentoml', 0.547683835029602, 'ml-ops', 2), ('microsoft/promptflow', 0.5460477471351624, 'llm', 0), ('tigerlab-ai/tiger', 0.5459373593330383, 'llm', 0... | 30 | 1 | null | 26.98 | 518 | 437 | 14 | 0 | 75 | 90 | 75 | 519 | 394 | 90 | 0.8 | 56 |
1,743 | llm | https://github.com/microsoft/llmlingua | ['inference', 'performance'] | null | [] | [] | null | null | null | microsoft/llmlingua | LLMLingua | 1,887 | 93 | 17 | Python | https://llmlingua.com/ | To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss. | microsoft | 2024-01-14 | 2023-07-07 | 29 | 63.811594 | https://avatars.githubusercontent.com/u/6154722?v=4 | To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss. | [] | ['inference', 'performance'] | 2024-01-13 | [('vllm-project/vllm', 0.6239213347434998, 'llm', 1), ('intel/intel-extension-for-transformers', 0.6135388016700745, 'perf', 0), ('lightning-ai/lit-gpt', 0.5566024780273438, 'llm', 0), ('bentoml/openllm', 0.5037171244621277, 'ml-ops', 0)] | 7 | 3 | null | 0.67 | 49 | 26 | 6 | 0 | 4 | 8 | 4 | 49 | 70 | 90 | 1.4 | 56 |
463 | ml-dl | https://github.com/pytorch/torchrec | [] | null | [] | [] | null | null | null | pytorch/torchrec | torchrec | 1,625 | 328 | 29 | Python | null | Pytorch domain library for recommendation systems | pytorch | 2024-01-14 | 2021-07-12 | 133 | 12.204936 | https://avatars.githubusercontent.com/u/21003710?v=4 | Pytorch domain library for recommendation systems | ['cuda', 'deep-learning', 'gpu', 'pytorch', 'recommendation-system', 'recommender-system', 'sharding'] | ['cuda', 'deep-learning', 'gpu', 'pytorch', 'recommendation-system', 'recommender-system', 'sharding'] | 2024-01-13 | [('rucaibox/recbole', 0.7371825575828552, 'ml', 3), ('nicolashug/surprise', 0.5874725580215454, 'ml', 0), ('pytorch/data', 0.5872920751571655, 'data', 0), ('pytorch/ignite', 0.5860687494277954, 'ml-dl', 2), ('pyg-team/pytorch_geometric', 0.570334255695343, 'ml-dl', 2), ('cvxgrp/pymde', 0.5692107677459717, 'ml', 3), ('b... | 198 | 5 | null | 9.6 | 194 | 142 | 30 | 0 | 5 | 4 | 5 | 194 | 572 | 90 | 2.9 | 56 |
1,541 | llm | https://github.com/weaviate/verba | ['retrieval-augmentation'] | null | [] | [] | null | null | null | weaviate/verba | Verba | 1,585 | 157 | 31 | Python | null | Retrieval Augmented Generation (RAG) chatbot powered by Weaviate | weaviate | 2024-01-14 | 2023-07-28 | 26 | 59.650538 | https://avatars.githubusercontent.com/u/37794290?v=4 | Retrieval Augmented Generation (RAG) chatbot powered by Weaviate | [] | ['retrieval-augmentation'] | 2024-01-02 | [('rcgai/simplyretrieve', 0.6520878076553345, 'llm', 0), ('embedchain/embedchain', 0.5736026167869568, 'llm', 0), ('microsoft/chatgpt-robot-manipulation-prompts', 0.5466259121894836, 'llm', 0), ('lm-sys/fastchat', 0.5395397543907166, 'llm', 0), ('openlmlab/moss', 0.5387402772903442, 'llm', 0), ('langchain-ai/chat-langc... | 8 | 1 | null | 2.92 | 91 | 51 | 6 | 0 | 3 | 6 | 3 | 91 | 196 | 90 | 2.2 | 56 |
290 | ml-ops | https://github.com/dagworks-inc/hamilton | ['mlops'] | null | [] | [] | null | null | null | dagworks-inc/hamilton | hamilton | 1,120 | 63 | 12 | Jupyter Notebook | https://hamilton.dagworks.io/en/latest/ | Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does. | dagworks-inc | 2024-01-13 | 2023-02-23 | 48 | 22.991202 | https://avatars.githubusercontent.com/u/116846391?v=4 | Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does. | ['dag', 'data-analysis', 'data-engineering', 'data-science', 'dataframe', 'etl', 'etl-framework', 'etl-pipeline', 'feature-engineering', 'featurization', 'lineage', 'llmops', 'machine-learning', 'mlops', 'numpy', 'orchestration', 'pandas', 'software-engineering'] | ['dag', 'data-analysis', 'data-engineering', 'data-science', 'dataframe', 'etl', 'etl-framework', 'etl-pipeline', 'feature-engineering', 'featurization', 'lineage', 'llmops', 'machine-learning', 'mlops', 'numpy', 'orchestration', 'pandas', 'software-engineering'] | 2024-01-13 | [('python-odin/odin', 0.6443514227867126, 'util', 0), ('polyaxon/datatile', 0.6286333203315735, 'pandas', 3), ('orchest/orchest', 0.6139141917228699, 'ml-ops', 5), ('mage-ai/mage-ai', 0.6080176830291748, 'ml-ops', 5), ('ploomber/ploomber', 0.6052381992340088, 'ml-ops', 4), ('fastai/fastcore', 0.603600263595581, 'util',... | 40 | 3 | null | 12.56 | 185 | 148 | 11 | 0 | 55 | 84 | 55 | 186 | 240 | 90 | 1.3 | 56 |
1,875 | llm | https://github.com/agenta-ai/agenta | ['llmops'] | null | [] | [] | null | null | null | agenta-ai/agenta | agenta | 623 | 126 | 13 | Python | http://www.agenta.ai | The all-in-one LLMOps platform: prompt management, evaluation, human feedback, and deployment all in one place. | agenta-ai | 2024-01-14 | 2023-04-26 | 39 | 15.630824 | https://avatars.githubusercontent.com/u/127993667?v=4 | The all-in-one LLMOps platform: prompt management, evaluation, human feedback, and deployment all in one place. | ['langchain', 'large-language-models', 'llama-index', 'llm', 'llm-evaluation', 'llm-framework', 'llm-tools', 'llmops', 'llms', 'prompt-engineering', 'prompt-management', 'prompt-toolkit', 'rag', 'rag-evaluation'] | ['langchain', 'large-language-models', 'llama-index', 'llm', 'llm-evaluation', 'llm-framework', 'llm-tools', 'llmops', 'llms', 'prompt-engineering', 'prompt-management', 'prompt-toolkit', 'rag', 'rag-evaluation'] | 2024-01-12 | [('confident-ai/deepeval', 0.690017819404602, 'testing', 3), ('hegelai/prompttools', 0.6764405965805054, 'llm', 3), ('eugeneyan/open-llms', 0.6486678719520569, 'study', 3), ('hwchase17/langchain', 0.6438751816749573, 'llm', 1), ('alpha-vllm/llama2-accessory', 0.6384699940681458, 'llm', 0), ('bentoml/openllm', 0.6264759... | 55 | 5 | null | 73.85 | 505 | 427 | 9 | 0 | 55 | 74 | 55 | 507 | 448 | 90 | 0.9 | 56 |
943 | ml | https://github.com/lutzroeder/netron | [] | null | [] | [] | null | null | null | lutzroeder/netron | netron | 25,153 | 2,629 | 296 | JavaScript | https://netron.app | Visualizer for neural network, deep learning and machine learning models | lutzroeder | 2024-01-14 | 2010-12-26 | 683 | 36.811834 | null | Visualizer for neural network, deep learning and machine learning models | ['ai', 'caffe', 'caffe2', 'coreml', 'darknet', 'deep-learning', 'deeplearning', 'keras', 'machine-learning', 'machinelearning', 'ml', 'mxnet', 'neural-network', 'onnx', 'paddle', 'pytorch', 'tensorflow', 'tensorflow-lite', 'torch', 'visualizer'] | ['ai', 'caffe', 'caffe2', 'coreml', 'darknet', 'deep-learning', 'deeplearning', 'keras', 'machine-learning', 'machinelearning', 'ml', 'mxnet', 'neural-network', 'onnx', 'paddle', 'pytorch', 'tensorflow', 'tensorflow-lite', 'torch', 'visualizer'] | 2024-01-14 | [('neuralmagic/sparseml', 0.6401857137680054, 'ml-dl', 4), ('roboflow/supervision', 0.6290085911750793, 'ml', 4), ('onnx/onnx', 0.616361141204834, 'ml', 9), ('mosaicml/composer', 0.6044427156448364, 'ml-dl', 4), ('rwightman/pytorch-image-models', 0.601951003074646, 'ml-dl', 1), ('ddbourgin/numpy-ml', 0.6000135540962219... | 1 | 1 | null | 21.67 | 76 | 65 | 159 | 0 | 2 | 0 | 2 | 76 | 87 | 90 | 1.1 | 55 |
423 | ml-dl | https://github.com/albumentations-team/albumentations | [] | null | [] | [] | null | null | null | albumentations-team/albumentations | albumentations | 13,001 | 1,564 | 130 | Python | https://albumentations.ai | Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125 | albumentations-team | 2024-01-13 | 2018-06-06 | 294 | 44.092539 | https://avatars.githubusercontent.com/u/57894582?v=4 | Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125 | ['augmentation', 'deep-learning', 'detection', 'fast-augmentations', 'image-augmentation', 'image-classification', 'image-processing', 'image-segmentation', 'machine-learning', 'object-detection', 'segmentation'] | ['augmentation', 'deep-learning', 'detection', 'fast-augmentations', 'image-augmentation', 'image-classification', 'image-processing', 'image-segmentation', 'machine-learning', 'object-detection', 'segmentation'] | 2023-12-07 | [('mdbloice/augmentor', 0.6705105900764465, 'ml', 3), ('facebookresearch/augly', 0.6632611751556396, 'data', 0), ('aleju/imgaug', 0.6503161787986755, 'ml', 4), ('open-mmlab/mmediting', 0.5985205769538879, 'ml', 2), ('fepegar/torchio', 0.5927706956863403, 'ml-dl', 3), ('deci-ai/super-gradients', 0.5558651685714722, 'ml-... | 133 | 3 | null | 0.35 | 41 | 15 | 68 | 1 | 1 | 3 | 1 | 41 | 31 | 90 | 0.8 | 55 |
647 | profiling | https://github.com/benfred/py-spy | [] | null | [] | [] | null | null | null | benfred/py-spy | py-spy | 11,366 | 429 | 112 | Rust | null | Sampling profiler for Python programs | benfred | 2024-01-13 | 2018-08-01 | 286 | 39.62251 | null | Sampling profiler for Python programs | ['performance-analysis', 'profiler', 'profiling'] | ['performance-analysis', 'profiler', 'profiling'] | 2023-12-16 | [('pythonspeed/filprofiler', 0.7144114971160889, 'profiling', 0), ('pyutils/line_profiler', 0.6891393065452576, 'profiling', 0), ('sumerc/yappi', 0.6047118902206421, 'profiling', 0), ('p403n1x87/austin', 0.5970548987388611, 'profiling', 1), ('joerick/pyinstrument', 0.5834751129150391, 'profiling', 1), ('pympler/pympler... | 37 | 3 | null | 0.46 | 48 | 16 | 66 | 1 | 0 | 6 | 6 | 48 | 41 | 90 | 0.9 | 55 |
1,119 | data | https://github.com/coleifer/peewee | [] | null | [] | [] | null | null | null | coleifer/peewee | peewee | 10,573 | 1,373 | 198 | Python | http://docs.peewee-orm.com/ | a small, expressive orm -- supports postgresql, mysql, sqlite and cockroachdb | coleifer | 2024-01-13 | 2010-10-11 | 694 | 15.231735 | null | a small, expressive orm -- supports postgresql, mysql, sqlite and cockroachdb | ['dank', 'gametight', 'peewee', 'sqlite'] | ['dank', 'gametight', 'peewee', 'sqlite'] | 2024-01-05 | [('mcfunley/pugsql', 0.6096048951148987, 'data', 0), ('ibis-project/ibis', 0.5938148498535156, 'data', 1), ('tiangolo/sqlmodel', 0.5841237306594849, 'data', 0), ('tiangolo/full-stack-fastapi-postgresql', 0.5561289191246033, 'template', 0), ('piccolo-orm/piccolo_admin', 0.5553250908851624, 'data', 1), ('aio-libs/aiopg',... | 153 | 3 | null | 1.83 | 42 | 42 | 161 | 0 | 5 | 14 | 5 | 42 | 84 | 90 | 2 | 55 |
5 | web | https://github.com/benoitc/gunicorn | [] | null | [] | [] | null | null | null | benoitc/gunicorn | gunicorn | 9,324 | 1,706 | 225 | Python | http://www.gunicorn.org | gunicorn 'Green Unicorn' is a WSGI HTTP Server for UNIX, fast clients and sleepy applications. | benoitc | 2024-01-14 | 2009-11-30 | 739 | 12.614612 | null | gunicorn 'Green Unicorn' is a WSGI HTTP Server for UNIX, fast clients and sleepy applications. | ['http', 'http-server', 'wsgi', 'wsgi-server'] | ['http', 'http-server', 'wsgi', 'wsgi-server'] | 2024-01-05 | [('pallets/werkzeug', 0.6659462451934814, 'web', 2), ('pylons/waitress', 0.6345184445381165, 'web', 2), ('bottlepy/bottle', 0.6153336763381958, 'web', 1), ('cherrypy/cherrypy', 0.5961728096008301, 'web', 2), ('pallets/flask', 0.5726903676986694, 'web', 1), ('pylons/pyramid', 0.5611777305603027, 'web', 1), ('encode/uvic... | 417 | 6 | null | 1.42 | 162 | 80 | 172 | 0 | 3 | 7 | 3 | 162 | 190 | 90 | 1.2 | 55 |
1,332 | nlp | https://github.com/google/sentencepiece | ['word-segmentation', 'tokeniser'] | null | [] | [] | 1 | null | null | google/sentencepiece | sentencepiece | 8,799 | 1,078 | 125 | C++ | null | Unsupervised text tokenizer for Neural Network-based text generation. | google | 2024-01-14 | 2017-03-07 | 360 | 24.441667 | https://avatars.githubusercontent.com/u/1342004?v=4 | Unsupervised text tokenizer for Neural Network-based text generation. | ['natural-language-processing', 'neural-machine-translation', 'word-segmentation'] | ['natural-language-processing', 'neural-machine-translation', 'tokeniser', 'word-segmentation'] | 2024-01-14 | [('minimaxir/textgenrnn', 0.6446799635887146, 'nlp', 0), ('huggingface/text-generation-inference', 0.607265830039978, 'llm', 0), ('google-research/electra', 0.5957339406013489, 'ml-dl', 0), ('lucidrains/deep-daze', 0.5594016909599304, 'ml', 0), ('sharonzhou/long_stable_diffusion', 0.5528421401977539, 'diffusion', 0), (... | 81 | 4 | null | 1.31 | 65 | 46 | 83 | 0 | 3 | 4 | 3 | 65 | 68 | 90 | 1 | 55 |
1,195 | llm | https://github.com/thudm/codegeex | [] | null | [] | [] | null | null | null | thudm/codegeex | CodeGeeX | 7,468 | 525 | 78 | Python | https://codegeex.cn | CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023) | thudm | 2024-01-13 | 2022-09-17 | 71 | 104.552 | https://avatars.githubusercontent.com/u/48590610?v=4 | CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023) | ['code-generation', 'pretrained-models', 'tools'] | ['code-generation', 'pretrained-models', 'tools'] | 2023-08-04 | [('salesforce/codet5', 0.6897627115249634, 'nlp', 1), ('salesforce/codegen', 0.6133092045783997, 'nlp', 0), ('bigcode-project/starcoder', 0.5817055106163025, 'llm', 1), ('ctlllll/llm-toolmaker', 0.5676085948944092, 'llm', 0), ('conceptofmind/toolformer', 0.5580187439918518, 'llm', 0), ('asottile/pyupgrade', 0.552376747... | 13 | 6 | null | 0.9 | 25 | 2 | 16 | 5 | 0 | 0 | 0 | 25 | 15 | 90 | 0.6 | 55 |
1,372 | web | https://github.com/reactive-python/reactpy | [] | ReactPy is a library for building user interfaces in Python without Javascript | [] | [] | null | null | null | reactive-python/reactpy | reactpy | 7,438 | 363 | 58 | Python | https://reactpy.dev | It's React, but in Python | reactive-python | 2024-01-13 | 2019-02-19 | 258 | 28.829457 | https://avatars.githubusercontent.com/u/106191177?v=4 | It's React, but in Python | ['javascript', 'react', 'reactpy'] | ['javascript', 'react', 'reactpy'] | 2023-12-28 | [('r0x0r/pywebview', 0.5532059073448181, 'gui', 1), ('webpy/webpy', 0.5520175695419312, 'web', 0), ('pyodide/pyodide', 0.5306482911109924, 'util', 0), ('urwid/urwid', 0.5233248472213745, 'term', 0)] | 21 | 4 | null | 2.15 | 35 | 12 | 60 | 1 | 12 | 23 | 12 | 35 | 50 | 90 | 1.4 | 55 |
680 | util | https://github.com/py-pdf/pypdf2 | [] | null | [] | [] | null | null | null | py-pdf/pypdf2 | pypdf | 6,900 | 1,301 | 148 | Python | https://pypdf.readthedocs.io/en/latest/ | A pure-python PDF library capable of splitting, merging, cropping, and transforming the pages of PDF files | py-pdf | 2024-01-14 | 2012-01-06 | 629 | 10.959837 | https://avatars.githubusercontent.com/u/102914013?v=4 | A pure-python PDF library capable of splitting, merging, cropping, and transforming the pages of PDF files | ['help-wanted', 'pdf', 'pdf-documents', 'pdf-manipulation', 'pdf-parser', 'pdf-parsing', 'pypdf2'] | ['help-wanted', 'pdf', 'pdf-documents', 'pdf-manipulation', 'pdf-parser', 'pdf-parsing', 'pypdf2'] | 2024-01-11 | [('pyfpdf/fpdf2', 0.6898808479309082, 'util', 1), ('jorisschellekens/borb', 0.6551130414009094, 'util', 1), ('camelot-dev/camelot', 0.6539286971092224, 'util', 0), ('pypdfium2-team/pypdfium2', 0.6358337998390198, 'util', 2), ('pdfminer/pdfminer.six', 0.5491688847541809, 'util', 1), ('unstructured-io/pipeline-paddleocr'... | 216 | 1 | null | 8.63 | 184 | 124 | 146 | 0 | 37 | 9 | 37 | 184 | 483 | 90 | 2.6 | 55 |
1,492 | llm | https://github.com/bigcode-project/starcoder | ['code-generation'] | null | [] | [] | null | null | null | bigcode-project/starcoder | starcoder | 6,776 | 476 | 65 | Python | null | Home of StarCoder: fine-tuning & inference! | bigcode-project | 2024-01-13 | 2023-04-24 | 40 | 168.797153 | https://avatars.githubusercontent.com/u/110470554?v=4 | Home of StarCoder: fine-tuning & inference! | [] | ['code-generation'] | 2023-06-29 | [('salesforce/codegen', 0.601254940032959, 'nlp', 0), ('huggingface/text-generation-inference', 0.5950606465339661, 'llm', 0), ('salesforce/codet5', 0.5859589576721191, 'nlp', 1), ('openai/image-gpt', 0.5846189260482788, 'llm', 0), ('thudm/codegeex', 0.5817055106163025, 'llm', 1), ('bytedance/lightseq', 0.5453761219978... | 8 | 3 | null | 1.31 | 16 | 1 | 9 | 7 | 0 | 0 | 0 | 16 | 10 | 90 | 0.6 | 55 |
20 | typing | https://github.com/facebook/pyre-check | ['code-quality'] | null | [] | [] | null | null | null | facebook/pyre-check | pyre-check | 6,597 | 477 | 110 | Python | https://pyre-check.org/ | Performant type-checking for python. | facebook | 2024-01-12 | 2017-11-10 | 324 | 20.325264 | https://avatars.githubusercontent.com/u/69631?v=4 | Performant type-checking for python. | ['abstract-interpretation', 'code-quality', 'control-flow-analysis', 'ocaml', 'program-analysis', 'security', 'static-analysis', 'taint-analysis', 'type-check', 'typechecker'] | ['abstract-interpretation', 'code-quality', 'control-flow-analysis', 'ocaml', 'program-analysis', 'security', 'static-analysis', 'taint-analysis', 'type-check', 'typechecker'] | 2024-01-12 | [('agronholm/typeguard', 0.8064729571342468, 'typing', 2), ('google/pytype', 0.7848848104476929, 'typing', 3), ('microsoft/pyright', 0.7650810480117798, 'typing', 2), ('instagram/monkeytype', 0.6643034815788269, 'typing', 1), ('python/mypy', 0.628227949142456, 'typing', 2), ('pydantic/pydantic', 0.6196001768112183, 'ut... | 254 | 2 | null | 29.19 | 13 | 4 | 75 | 0 | 1 | 14 | 1 | 13 | 21 | 90 | 1.6 | 55 |
70 | util | https://github.com/pygithub/pygithub | [] | null | [] | [] | null | null | null | pygithub/pygithub | PyGithub | 6,469 | 1,713 | 111 | Python | https://pygithub.readthedocs.io/ | Typed interactions with the GitHub API v3 | pygithub | 2024-01-13 | 2012-02-25 | 622 | 10.39316 | https://avatars.githubusercontent.com/u/11288996?v=4 | Typed interactions with the GitHub API v3 | ['github', 'github-api', 'pygithub'] | ['github', 'github-api', 'pygithub'] | 2024-01-01 | [('fastai/ghapi', 0.5488420724868774, 'util', 2)] | 346 | 4 | null | 4 | 103 | 47 | 145 | 0 | 10 | 9 | 10 | 103 | 179 | 90 | 1.7 | 55 |
1,814 | study | https://github.com/mrdbourke/pytorch-deep-learning | [] | null | [] | [] | null | null | null | mrdbourke/pytorch-deep-learning | pytorch-deep-learning | 6,384 | 2,082 | 88 | Jupyter Notebook | https://learnpytorch.io | Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course. | mrdbourke | 2024-01-14 | 2021-10-19 | 119 | 53.647059 | null | Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course. | ['deep-learning', 'machine-learning', 'pytorch'] | ['deep-learning', 'machine-learning', 'pytorch'] | 2024-01-11 | [('pytorch/ignite', 0.7811650037765503, 'ml-dl', 3), ('mrdbourke/tensorflow-deep-learning', 0.7342724800109863, 'study', 1), ('skorch-dev/skorch', 0.6955669522285461, 'ml-dl', 2), ('pyg-team/pytorch_geometric', 0.6894313097000122, 'ml-dl', 2), ('rasbt/machine-learning-book', 0.6849406957626343, 'study', 3), ('mrdbourke... | 42 | 3 | null | 2.42 | 41 | 9 | 27 | 0 | 0 | 0 | 0 | 41 | 27 | 90 | 0.7 | 55 |
1,177 | diffusion | https://github.com/openai/consistency_models | [] | null | [] | [] | null | null | null | openai/consistency_models | consistency_models | 5,787 | 379 | 60 | Python | null | Official repo for consistency models. | openai | 2024-01-13 | 2023-02-26 | 48 | 119.849112 | https://avatars.githubusercontent.com/u/14957082?v=4 | Official repo for consistency models. | [] | [] | 2023-08-12 | [] | 9 | 7 | null | 0.23 | 18 | 1 | 11 | 5 | 0 | 0 | 0 | 18 | 16 | 90 | 0.9 | 55 |
1,081 | util | https://github.com/buildbot/buildbot | [] | null | [] | [] | null | null | null | buildbot/buildbot | buildbot | 5,127 | 1,655 | 199 | Python | https://www.buildbot.net | Python-based continuous integration testing framework; your pull requests are more than welcome! | buildbot | 2024-01-14 | 2010-07-06 | 708 | 7.241525 | https://avatars.githubusercontent.com/u/324515?v=4 | Python-based continuous integration testing framework; your pull requests are more than welcome! | ['ci', 'ci-framework', 'continuous-integration'] | ['ci', 'ci-framework', 'continuous-integration'] | 2024-01-09 | [('eleutherai/pyfra', 0.6259655952453613, 'ml', 0), ('nedbat/coveragepy', 0.57981938123703, 'testing', 0), ('wolever/parameterized', 0.5751279592514038, 'testing', 0), ('willmcgugan/textual', 0.5555017590522766, 'term', 0), ('masoniteframework/masonite', 0.549967885017395, 'web', 0), ('cobrateam/splinter', 0.5403817296... | 856 | 5 | null | 22.69 | 255 | 203 | 165 | 0 | 6 | 13 | 6 | 255 | 235 | 90 | 0.9 | 55 |
98 | jupyter | https://github.com/voila-dashboards/voila | [] | null | [] | [] | null | null | null | voila-dashboards/voila | voila | 5,051 | 487 | 77 | Python | https://voila.readthedocs.io | Voilà turns Jupyter notebooks into standalone web applications | voila-dashboards | 2024-01-14 | 2018-08-21 | 284 | 17.785211 | https://avatars.githubusercontent.com/u/55792893?v=4 | Voilà turns Jupyter notebooks into standalone web applications | ['dashboarding', 'jupyter', 'jupyter-notebook', 'jupyterlab-extension'] | ['dashboarding', 'jupyter', 'jupyter-notebook', 'jupyterlab-extension'] | 2024-01-11 | [('jupyterlab/jupyterlab-desktop', 0.7262636423110962, 'jupyter', 2), ('jupyter-widgets/ipywidgets', 0.7114137411117554, 'jupyter', 1), ('jupyter/notebook', 0.6948908567428589, 'jupyter', 2), ('jupyterlite/jupyterlite', 0.6913954615592957, 'jupyter', 2), ('aws/graph-notebook', 0.6807038187980652, 'jupyter', 2), ('mwout... | 68 | 4 | null | 1.71 | 41 | 22 | 66 | 0 | 18 | 32 | 18 | 41 | 66 | 90 | 1.6 | 55 |
257 | crypto | https://github.com/ethereum/web3.py | [] | null | [] | [] | 1 | null | null | ethereum/web3.py | web3.py | 4,591 | 1,654 | 119 | Python | http://web3py.readthedocs.io | A python interface for interacting with the Ethereum blockchain and ecosystem. | ethereum | 2024-01-14 | 2016-04-14 | 406 | 11.288022 | https://avatars.githubusercontent.com/u/6250754?v=4 | A python interface for interacting with the Ethereum blockchain and ecosystem. | [] | [] | 2024-01-10 | [('primal100/pybitcointools', 0.6811222434043884, 'crypto', 0), ('ethereum/py-evm', 0.6437891721725464, 'crypto', 0), ('gbeced/basana', 0.6058024168014526, 'finance', 0), ('1200wd/bitcoinlib', 0.6057431101799011, 'crypto', 0), ('willmcgugan/textual', 0.5721923112869263, 'term', 0), ('gbeced/pyalgotrade', 0.570094883441... | 249 | 4 | null | 9.17 | 106 | 76 | 94 | 0 | 0 | 27 | 27 | 106 | 104 | 90 | 1 | 55 |
1,842 | llm | https://github.com/langchain-ai/chat-langchain | ['rag', 'question-answering', 'docs'] | Locally hosted chatbot specifically focused on question answering over the LangChain documentation | [] | [] | null | null | null | langchain-ai/chat-langchain | chat-langchain | 4,229 | 1,008 | 46 | Python | https://chat.langchain.com | null | langchain-ai | 2024-01-13 | 2023-01-16 | 54 | 78.108179 | https://avatars.githubusercontent.com/u/126733545?v=4 | Locally hosted chatbot specifically focused on question answering over the LangChain documentation | [] | ['docs', 'question-answering', 'rag'] | 2024-01-11 | [('lm-sys/fastchat', 0.628669023513794, 'llm', 0), ('togethercomputer/openchatkit', 0.6002198457717896, 'nlp', 0), ('embedchain/embedchain', 0.5953378677368164, 'llm', 0), ('nomic-ai/gpt4all', 0.594020426273346, 'llm', 0), ('mayooear/gpt4-pdf-chatbot-langchain', 0.5839036107063293, 'llm', 0), ('gunthercox/chatterbot-co... | 16 | 1 | null | 2.63 | 51 | 35 | 12 | 0 | 0 | 0 | 0 | 51 | 56 | 90 | 1.1 | 55 |
1,239 | llm | https://github.com/togethercomputer/redpajama-data | [] | null | [] | [] | null | null | null | togethercomputer/redpajama-data | RedPajama-Data | 4,058 | 321 | 78 | Python | null | The RedPajama-Data repository contains code for preparing large datasets for training large language models. | togethercomputer | 2024-01-13 | 2023-04-14 | 41 | 97.61512 | https://avatars.githubusercontent.com/u/109101822?v=4 | The RedPajama-Data repository contains code for preparing large datasets for training large language models. | [] | [] | 2023-12-27 | [('hannibal046/awesome-llm', 0.6528944969177246, 'study', 0), ('yueyu1030/attrprompt', 0.6486657857894897, 'llm', 0), ('freedomintelligence/llmzoo', 0.6302767992019653, 'llm', 0), ('bigscience-workshop/biomedical', 0.6301681995391846, 'data', 0), ('eleutherai/the-pile', 0.6279685497283936, 'data', 0), ('cg123/mergekit'... | 8 | 3 | null | 0.54 | 28 | 18 | 9 | 1 | 0 | 0 | 0 | 28 | 39 | 90 | 1.4 | 55 |
504 | ml-ops | https://github.com/adap/flower | [] | null | [] | [] | null | null | null | adap/flower | flower | 3,479 | 686 | 33 | Python | https://flower.dev | Flower: A Friendly Federated Learning Framework | adap | 2024-01-14 | 2020-02-17 | 206 | 16.876646 | https://avatars.githubusercontent.com/u/57905187?v=4 | Flower: A Friendly Federated Learning Framework | ['ai', 'android', 'artificial-intelligence', 'cpp', 'deep-learning', 'federated-analytics', 'federated-learning', 'federated-learning-framework', 'fleet-intelligence', 'fleet-learning', 'flower', 'framework', 'grpc', 'ios', 'machine-learning', 'pytorch', 'raspberry-pi', 'scikit-learn', 'tensorflow'] | ['ai', 'android', 'artificial-intelligence', 'cpp', 'deep-learning', 'federated-analytics', 'federated-learning', 'federated-learning-framework', 'fleet-intelligence', 'fleet-learning', 'flower', 'framework', 'grpc', 'ios', 'machine-learning', 'pytorch', 'raspberry-pi', 'scikit-learn', 'tensorflow'] | 2024-01-08 | [('nevronai/metisfl', 0.8411728739738464, 'ml', 6), ('jonasgeiping/breaching', 0.6508305668830872, 'ml', 3), ('horovod/horovod', 0.6284599304199219, 'ml-ops', 4), ('nccr-itmo/fedot', 0.618629515171051, 'ml-ops', 1), ('tensorflow/tensorflow', 0.6108560562133789, 'ml-dl', 3), ('mlflow/mlflow', 0.5906698107719421, 'ml-ops... | 97 | 3 | null | 14.02 | 360 | 260 | 48 | 0 | 5 | 4 | 5 | 359 | 210 | 90 | 0.6 | 55 |
1,710 | perf | https://github.com/facebookincubator/cinder | ['cpython'] | null | [] | [] | null | null | null | facebookincubator/cinder | cinder | 3,301 | 121 | 60 | Python | https://trycinder.com | Cinder is Meta's internal performance-oriented production version of CPython. | facebookincubator | 2024-01-14 | 2021-03-16 | 150 | 22.006667 | https://avatars.githubusercontent.com/u/19538647?v=4 | Cinder is Meta's internal performance-oriented production version of CPython. | ['compiler', 'interpreter', 'jit', 'runtime'] | ['compiler', 'cpython', 'interpreter', 'jit', 'runtime'] | 2024-01-13 | [('rustpython/rustpython', 0.5831960439682007, 'util', 3), ('python/cpython', 0.5806695222854614, 'util', 1), ('faster-cpython/ideas', 0.5721518397331238, 'perf', 1), ('faster-cpython/tools', 0.5622638463973999, 'perf', 1), ('pypy/pypy', 0.5570579767227173, 'util', 2), ('brandtbucher/specialist', 0.5538285374641418, 'p... | 1,760 | 6 | null | 7.19 | 10 | 8 | 34 | 0 | 0 | 0 | 0 | 12 | 14 | 90 | 1.2 | 55 |
1,293 | llm | https://github.com/microsoft/lmops | [] | null | [] | [] | null | null | null | microsoft/lmops | LMOps | 2,828 | 192 | 55 | Python | https://aka.ms/GeneralAI | General technology for enabling AI capabilities w/ LLMs and MLLMs | microsoft | 2024-01-13 | 2022-12-13 | 59 | 47.932203 | https://avatars.githubusercontent.com/u/6154722?v=4 | General technology for enabling AI capabilities w/ LLMs and MLLMs | ['agi', 'gpt', 'language-model', 'llm', 'lm', 'lmops', 'nlp', 'pretraining', 'prompt', 'promptist', 'x-prompt'] | ['agi', 'gpt', 'language-model', 'llm', 'lm', 'lmops', 'nlp', 'pretraining', 'prompt', 'promptist', 'x-prompt'] | 2024-01-02 | [('mlc-ai/mlc-llm', 0.7063540816307068, 'llm', 2), ('microsoft/promptflow', 0.6579537987709045, 'llm', 3), ('prefecthq/marvin', 0.6434080600738525, 'nlp', 2), ('lastmile-ai/aiconfig', 0.6332518458366394, 'util', 1), ('bentoml/bentoml', 0.6321725249290466, 'ml-ops', 1), ('cheshire-cat-ai/core', 0.6224048137664795, 'llm'... | 22 | 4 | null | 1.54 | 68 | 54 | 13 | 0 | 0 | 0 | 0 | 68 | 95 | 90 | 1.4 | 55 |
51 | testing | https://github.com/nedbat/coveragepy | [] | null | [] | [] | null | null | null | nedbat/coveragepy | coveragepy | 2,742 | 392 | 32 | Python | https://coverage.readthedocs.io | The code coverage tool for Python | nedbat | 2024-01-12 | 2018-06-23 | 292 | 9.376649 | null | The code coverage tool for Python | [] | [] | 2024-01-13 | [('eugeneyan/python-collab-template', 0.6858402490615845, 'template', 0), ('wolever/parameterized', 0.6841293573379517, 'testing', 0), ('pytest-dev/pytest-bdd', 0.6206257939338684, 'testing', 0), ('ionelmc/pytest-benchmark', 0.6183704733848572, 'testing', 0), ('eleutherai/pyfra', 0.6178824305534363, 'ml', 0), ('pmoriss... | 168 | 6 | null | 8.23 | 55 | 30 | 68 | 0 | 15 | 23 | 15 | 55 | 138 | 90 | 2.5 | 55 |
1,281 | viz | https://github.com/pyvista/pyvista | [] | null | [] | [] | null | null | null | pyvista/pyvista | pyvista | 2,144 | 407 | 34 | Python | https://docs.pyvista.org | 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK) | pyvista | 2024-01-14 | 2017-05-31 | 347 | 6.16345 | https://avatars.githubusercontent.com/u/50384771?v=4 | 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK) | ['3d', 'mesh', 'mesh-processing', 'meshviewer', 'open-science', 'plotting', 'scientific-research', 'scientific-visualization', 'visualization', 'vtk'] | ['3d', 'mesh', 'mesh-processing', 'meshviewer', 'open-science', 'plotting', 'scientific-research', 'scientific-visualization', 'visualization', 'vtk'] | 2024-01-13 | [('marcomusy/vedo', 0.7296451330184937, 'viz', 6), ('pyqtgraph/pyqtgraph', 0.6187593936920166, 'viz', 2), ('contextlab/hypertools', 0.5857540369033813, 'ml', 1), ('enthought/mayavi', 0.5794352293014526, 'viz', 2), ('districtdatalabs/yellowbrick', 0.578895092010498, 'ml', 1), ('holoviz/hvplot', 0.5786033868789673, 'pand... | 153 | 4 | null | 15.13 | 391 | 278 | 81 | 0 | 12 | 19 | 12 | 390 | 1,158 | 90 | 3 | 55 |
371 | gis | https://github.com/microsoft/torchgeo | [] | null | [] | [] | null | null | null | microsoft/torchgeo | torchgeo | 2,046 | 247 | 45 | Python | https://torchgeo.rtfd.io | TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data | microsoft | 2024-01-12 | 2021-05-21 | 140 | 14.554878 | https://avatars.githubusercontent.com/u/6154722?v=4 | TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data | ['computer-vision', 'datasets', 'deep-learning', 'earth-observation', 'geospatial', 'models', 'pytorch', 'remote-sensing', 'satellite-imagery', 'torchvision', 'transforms'] | ['computer-vision', 'datasets', 'deep-learning', 'earth-observation', 'geospatial', 'models', 'pytorch', 'remote-sensing', 'satellite-imagery', 'torchvision', 'transforms'] | 2024-01-12 | [('datasystemslab/geotorch', 0.6509654521942139, 'gis', 1), ('developmentseed/label-maker', 0.629837691783905, 'gis', 4), ('remotesensinglab/raster4ml', 0.6221429705619812, 'gis', 1), ('azavea/raster-vision', 0.6176372766494751, 'gis', 5), ('osgeo/grass', 0.6095272302627563, 'gis', 3), ('huggingface/datasets', 0.570610... | 53 | 7 | null | 10.5 | 171 | 132 | 32 | 0 | 4 | 4 | 4 | 171 | 261 | 90 | 1.5 | 55 |
765 | nlp | https://github.com/huggingface/setfit | [] | null | [] | [] | null | null | null | huggingface/setfit | setfit | 1,804 | 185 | 21 | Jupyter Notebook | https://hf.co/docs/setfit | Efficient few-shot learning with Sentence Transformers | huggingface | 2024-01-13 | 2022-06-30 | 82 | 21.810017 | https://avatars.githubusercontent.com/u/25720743?v=4 | Efficient few-shot learning with Sentence Transformers | ['few-shot-learning', 'nlp', 'sentence-transformers'] | ['few-shot-learning', 'nlp', 'sentence-transformers'] | 2024-01-11 | [('eleutherai/lm-evaluation-harness', 0.6814461350440979, 'llm', 0), ('alibaba/easynlp', 0.5513603091239929, 'nlp', 1), ('ofa-sys/ofa', 0.5320513844490051, 'llm', 0), ('bigscience-workshop/t-zero', 0.5152558088302612, 'llm', 0), ('google-research/electra', 0.5080073475837708, 'ml-dl', 1)] | 48 | 4 | null | 4.63 | 110 | 86 | 19 | 0 | 5 | 9 | 5 | 110 | 182 | 90 | 1.7 | 55 |
1,572 | llm | https://github.com/pathwaycom/llm-app | [] | null | [] | [] | null | null | null | pathwaycom/llm-app | llm-app | 1,568 | 101 | 21 | Python | https://pathway.com/developers/showcases/llm-app-pathway/ | LLM App is a production framework for building and serving AI applications and LLM-enabled real-time data pipelines. | pathwaycom | 2024-01-13 | 2023-07-19 | 27 | 56.287179 | https://avatars.githubusercontent.com/u/25750857?v=4 | LLM App is a production framework for building and serving AI applications and LLM-enabled real-time data pipelines. | ['chatbot', 'hugging-face', 'llm', 'llm-local', 'llm-prompting', 'llm-security', 'llmops', 'machine-learning', 'open-ai', 'pathway', 'rag', 'real-time', 'retrieval-augmented-generation', 'vector-database', 'vector-index'] | ['chatbot', 'hugging-face', 'llm', 'llm-local', 'llm-prompting', 'llm-security', 'llmops', 'machine-learning', 'open-ai', 'pathway', 'rag', 'real-time', 'retrieval-augmented-generation', 'vector-database', 'vector-index'] | 2023-12-27 | [('microsoft/semantic-kernel', 0.7631767988204956, 'llm', 1), ('microsoft/promptflow', 0.7594974040985107, 'llm', 1), ('deepset-ai/haystack', 0.7468881607055664, 'llm', 1), ('cheshire-cat-ai/core', 0.6957066059112549, 'llm', 2), ('deep-diver/llm-as-chatbot', 0.6957004070281982, 'llm', 1), ('embedchain/embedchain', 0.67... | 15 | 5 | null | 2.19 | 7 | 4 | 6 | 1 | 8 | 16 | 8 | 7 | 6 | 90 | 0.9 | 55 |
1,767 | ml-ops | https://github.com/meltano/meltano | [] | null | [] | [] | null | null | null | meltano/meltano | meltano | 1,447 | 139 | 13 | Python | https://meltano.com/ | Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations. | meltano | 2024-01-14 | 2021-06-21 | 136 | 10.628541 | https://avatars.githubusercontent.com/u/43816713?v=4 | Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations. | ['connectors', 'data', 'data-engineering', 'data-pipelines', 'dataops', 'dataops-platform', 'elt', 'extract-data', 'integration', 'loaders', 'meltano', 'meltano-sdk', 'open-source', 'opensource', 'pipelines', 'singer', 'tap', 'taps', 'target', 'targets'] | ['connectors', 'data', 'data-engineering', 'data-pipelines', 'dataops', 'dataops-platform', 'elt', 'extract-data', 'integration', 'loaders', 'meltano', 'meltano-sdk', 'open-source', 'opensource', 'pipelines', 'singer', 'tap', 'taps', 'target', 'targets'] | 2024-01-12 | [('mage-ai/mage-ai', 0.6557142734527588, 'ml-ops', 5), ('airbytehq/airbyte', 0.6305922865867615, 'data', 3), ('ploomber/ploomber', 0.6284797787666321, 'ml-ops', 2), ('orchest/orchest', 0.6131107211112976, 'ml-ops', 2), ('simonw/datasette', 0.6087267398834229, 'data', 0), ('avaiga/taipy', 0.608718752861023, 'data', 2), ... | 157 | 4 | null | 20.71 | 143 | 110 | 31 | 0 | 19 | 106 | 19 | 143 | 296 | 90 | 2.1 | 55 |
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