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1,466 | util | https://github.com/lcompilers/lpython | [] | null | [] | [] | null | null | null | lcompilers/lpython | lpython | 1,175 | 122 | 28 | C++ | https://lpython.org/ | Python compiler | lcompilers | 2024-01-12 | 2021-12-29 | 108 | 10.793963 | https://avatars.githubusercontent.com/u/96538276?v=4 | Python compiler | ['compiler', 'high-performance'] | ['compiler', 'high-performance'] | 2024-01-11 | [('exaloop/codon', 0.7257847189903259, 'perf', 2), ('cython/cython', 0.6913489699363708, 'util', 0), ('pypy/pypy', 0.6041545271873474, 'util', 1), ('numba/numba', 0.603155255317688, 'perf', 1), ('pyston/pyston', 0.6024731397628784, 'util', 0), ('klen/py-frameworks-bench', 0.587522566318512, 'perf', 0), ('markshannon/fa... | 65 | 6 | null | 30.87 | 97 | 58 | 25 | 0 | 11 | 12 | 11 | 97 | 217 | 90 | 2.2 | 55 |
1,835 | llm | https://github.com/hao-ai-lab/lookaheaddecoding | ['decoding', 'lookahead'] | Break the Sequential Dependency of LLM Inference Using Lookahead Decoding | [] | [] | null | null | null | hao-ai-lab/lookaheaddecoding | LookaheadDecoding | 802 | 49 | 9 | Python | null | null | hao-ai-lab | 2024-01-14 | 2023-11-21 | 10 | 80.2 | https://avatars.githubusercontent.com/u/149045815?v=4 | Break the Sequential Dependency of LLM Inference Using Lookahead Decoding | [] | ['decoding', 'lookahead'] | 2024-01-09 | [('karpathy/llama2.c', 0.5412218570709229, 'llm', 0), ('facebookresearch/llama', 0.5299458503723145, 'llm', 0), ('artidoro/qlora', 0.5174603462219238, 'llm', 0), ('facebookresearch/codellama', 0.5007719397544861, 'llm', 0)] | 5 | 2 | null | 0.31 | 44 | 24 | 2 | 0 | 0 | 0 | 0 | 44 | 175 | 90 | 4 | 55 |
499 | ml | https://github.com/ageron/handson-ml2 | [] | null | [] | [] | null | null | null | ageron/handson-ml2 | handson-ml2 | 26,281 | 12,333 | 648 | Jupyter Notebook | null | A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2. | ageron | 2024-01-14 | 2019-01-08 | 264 | 99.549242 | null | A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2. | [] | [] | 2023-02-04 | [('fchollet/deep-learning-with-python-notebooks', 0.8291416168212891, 'study', 0), ('jakevdp/pythondatasciencehandbook', 0.6813152432441711, 'study', 0), ('gradio-app/gradio', 0.6595058441162109, 'viz', 0), ('rasbt/machine-learning-book', 0.6461301445960999, 'study', 0), ('firmai/industry-machine-learning', 0.642495632... | 75 | 2 | null | 0.04 | 6 | 2 | 61 | 11 | 0 | 0 | 0 | 6 | 7 | 90 | 1.2 | 54 |
671 | ml-dl | https://github.com/facebookresearch/detectron | [] | null | [] | [] | null | null | null | facebookresearch/detectron | Detectron | 26,066 | 5,568 | 944 | Python | null | FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet. | facebookresearch | 2024-01-14 | 2017-10-05 | 329 | 79.056326 | https://avatars.githubusercontent.com/u/16943930?v=4 | FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet. | [] | [] | 2023-10-19 | [('matterport/mask_rcnn', 0.5304756760597229, 'ml-dl', 0), ('open-mmlab/mmdetection', 0.5015984177589417, 'ml', 0)] | 43 | 3 | null | 0.12 | 2 | 0 | 76 | 3 | 0 | 0 | 0 | 2 | 2 | 90 | 1 | 54 |
1,243 | ml | https://github.com/jindongwang/transferlearning | [] | null | [] | [] | null | null | null | jindongwang/transferlearning | transferlearning | 12,474 | 3,731 | 336 | Python | http://transferlearning.xyz/ | Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习 | jindongwang | 2024-01-14 | 2017-04-30 | 352 | 35.408759 | null | Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习 | ['deep-learning', 'domain-adaptation', 'domain-adaption', 'domain-generalization', 'few-shot', 'few-shot-learning', 'generalization', 'machine-learning', 'meta-learning', 'paper', 'papers', 'representation-learning', 'self-supervised-learning', 'style-transfer', 'survey', 'theory', 'transfer-learning', 'transferlearnin... | ['deep-learning', 'domain-adaptation', 'domain-adaption', 'domain-generalization', 'few-shot', 'few-shot-learning', 'generalization', 'machine-learning', 'meta-learning', 'paper', 'papers', 'representation-learning', 'self-supervised-learning', 'style-transfer', 'survey', 'theory', 'transfer-learning', 'transferlearnin... | 2024-01-08 | [('amanchadha/coursera-deep-learning-specialization', 0.5513812899589539, 'study', 1), ('huggingface/autotrain-advanced', 0.5214440822601318, 'ml', 2), ('patchy631/machine-learning', 0.5060864090919495, 'ml', 0), ('alirezadir/machine-learning-interview-enlightener', 0.5019001364707947, 'study', 2), ('udacity/deep-learn... | 40 | 4 | null | 0.96 | 14 | 7 | 82 | 0 | 0 | 0 | 0 | 14 | 22 | 90 | 1.6 | 54 |
425 | ml-dl | https://github.com/facebookresearch/detr | [] | null | [] | [] | null | null | null | facebookresearch/detr | detr | 12,338 | 2,222 | 149 | Python | null | End-to-End Object Detection with Transformers | facebookresearch | 2024-01-14 | 2020-05-26 | 192 | 64.260417 | https://avatars.githubusercontent.com/u/16943930?v=4 | End-to-End Object Detection with Transformers | [] | [] | 2023-02-07 | [('cvg/lightglue', 0.5226452350616455, 'ml-dl', 0), ('nvlabs/gcvit', 0.5166937112808228, 'diffusion', 0), ('matterport/mask_rcnn', 0.5123329758644104, 'ml-dl', 0)] | 26 | 7 | null | 0.02 | 36 | 7 | 44 | 11 | 0 | 0 | 0 | 36 | 47 | 90 | 1.3 | 54 |
1,380 | ml | https://github.com/microsoft/swin-transformer | [] | null | [] | [] | null | null | null | microsoft/swin-transformer | Swin-Transformer | 12,319 | 1,937 | 125 | Python | https://arxiv.org/abs/2103.14030 | This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows". | microsoft | 2024-01-14 | 2021-03-25 | 148 | 82.836695 | https://avatars.githubusercontent.com/u/6154722?v=4 | This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows". | ['ade20k', 'image-classification', 'imagenet', 'mask-rcnn', 'mscoco', 'object-detection', 'semantic-segmentation', 'swin-transformer'] | ['ade20k', 'image-classification', 'imagenet', 'mask-rcnn', 'mscoco', 'object-detection', 'semantic-segmentation', 'swin-transformer'] | 2023-08-16 | [('nvlabs/gcvit', 0.6548908352851868, 'diffusion', 4), ('google-research/maxvit', 0.5897934436798096, 'ml', 1), ('lucidrains/vit-pytorch', 0.5670905113220215, 'ml-dl', 1), ('open-mmlab/mmdetection', 0.5538708567619324, 'ml', 3), ('deci-ai/super-gradients', 0.5506076812744141, 'ml-dl', 4), ('open-mmlab/mmsegmentation', ... | 13 | 8 | null | 0.02 | 20 | 3 | 34 | 5 | 0 | 0 | 0 | 20 | 11 | 90 | 0.6 | 54 |
85 | ml | https://github.com/statsmodels/statsmodels | [] | null | [] | [] | null | null | null | statsmodels/statsmodels | statsmodels | 9,210 | 2,836 | 279 | Python | http://www.statsmodels.org/devel/ | Statsmodels: statistical modeling and econometrics in Python | statsmodels | 2024-01-13 | 2011-06-12 | 659 | 13.969664 | https://avatars.githubusercontent.com/u/717666?v=4 | Statsmodels: statistical modeling and econometrics in Python | ['count-model', 'data-analysis', 'data-science', 'econometrics', 'forecasting', 'generalized-linear-models', 'hypothesis-testing', 'prediction', 'regression-models', 'robust-estimation', 'statistics', 'timeseries-analysis'] | ['count-model', 'data-analysis', 'data-science', 'econometrics', 'forecasting', 'generalized-linear-models', 'hypothesis-testing', 'prediction', 'regression-models', 'robust-estimation', 'statistics', 'timeseries-analysis'] | 2024-01-04 | [('firmai/atspy', 0.6599208116531372, 'time-series', 1), ('ranaroussi/quantstats', 0.6285594701766968, 'finance', 0), ('alkaline-ml/pmdarima', 0.6218242645263672, 'time-series', 2), ('scikit-learn/scikit-learn', 0.6116586327552795, 'ml', 3), ('scikit-mobility/scikit-mobility', 0.5975031852722168, 'gis', 3), ('bashtage/... | 421 | 2 | null | 6.69 | 232 | 140 | 153 | 0 | 3 | 4 | 3 | 232 | 184 | 90 | 0.8 | 54 |
528 | util | https://github.com/facebookresearch/hydra | [] | null | [] | [] | null | null | null | facebookresearch/hydra | hydra | 7,864 | 616 | 124 | Python | https://hydra.cc | Hydra is a framework for elegantly configuring complex applications | facebookresearch | 2024-01-14 | 2019-06-12 | 241 | 32.515062 | https://avatars.githubusercontent.com/u/16943930?v=4 | Hydra is a framework for elegantly configuring complex applications | [] | [] | 2023-11-30 | [('ashleve/lightning-hydra-template', 0.5850319266319275, 'util', 0), ('google/gin-config', 0.5556942224502563, 'util', 0), ('willmcgugan/textual', 0.5213847160339355, 'term', 0), ('alphasecio/langchain-examples', 0.5024363994598389, 'llm', 0)] | 114 | 3 | null | 0.63 | 69 | 20 | 56 | 2 | 1 | 5 | 1 | 69 | 142 | 90 | 2.1 | 54 |
1,192 | util | https://github.com/xonsh/xonsh | ['shell'] | null | [] | [] | null | null | null | xonsh/xonsh | xonsh | 7,471 | 633 | 105 | Python | http://xon.sh | :shell: Python-powered, cross-platform, Unix-gazing shell. | xonsh | 2024-01-14 | 2015-01-21 | 470 | 15.866808 | https://avatars.githubusercontent.com/u/17418188?v=4 | :shell: Python-powered, cross-platform, Unix-gazing shell. | ['bash', 'cli', 'command-line', 'console', 'devops', 'fish', 'iterm2', 'prompt', 'python-shell', 'script', 'shell', 'terminal', 'windows-terminal', 'xonsh', 'zsh'] | ['bash', 'cli', 'command-line', 'console', 'devops', 'fish', 'iterm2', 'prompt', 'python-shell', 'script', 'shell', 'terminal', 'windows-terminal', 'xonsh', 'zsh'] | 2023-12-31 | [('tiangolo/typer', 0.614140510559082, 'term', 3), ('kellyjonbrazil/jc', 0.5756747722625732, 'util', 3), ('jquast/blessed', 0.569438099861145, 'term', 2), ('pygamelib/pygamelib', 0.5624502301216125, 'gamedev', 0), ('urwid/urwid', 0.5422582030296326, 'term', 0), ('pypy/pypy', 0.5222761631011963, 'util', 0), ('tmbo/quest... | 320 | 2 | null | 1.9 | 64 | 34 | 109 | 0 | 4 | 14 | 4 | 64 | 118 | 90 | 1.8 | 54 |
1,274 | util | https://github.com/googleapis/google-api-python-client | [] | null | [] | [] | null | null | null | googleapis/google-api-python-client | google-api-python-client | 7,135 | 2,452 | 284 | Python | https://googleapis.github.io/google-api-python-client/docs/ | 🐍 The official Python client library for Google's discovery based APIs. | googleapis | 2024-01-13 | 2014-01-08 | 524 | 13.594175 | https://avatars.githubusercontent.com/u/16785467?v=4 | 🐍 The official Python client library for Google's discovery based APIs. | [] | [] | 2024-01-09 | [('nv7-github/googlesearch', 0.6702570915222168, 'util', 0), ('dsdanielpark/bard-api', 0.6036682724952698, 'llm', 0), ('openai/openai-python', 0.5968145728111267, 'util', 0), ('dialogflow/dialogflow-python-client-v2', 0.5611771941184998, 'nlp', 0), ('radiantearth/radiant-mlhub', 0.5603718757629395, 'gis', 0), ('typesen... | 190 | 3 | null | 2.69 | 79 | 55 | 122 | 0 | 41 | 18 | 41 | 77 | 84 | 90 | 1.1 | 54 |
44 | ml | https://github.com/lmcinnes/umap | [] | null | [] | [] | null | null | null | lmcinnes/umap | umap | 6,678 | 754 | 128 | Python | null | Uniform Manifold Approximation and Projection | lmcinnes | 2024-01-14 | 2017-07-02 | 343 | 19.453184 | null | Uniform Manifold Approximation and Projection | ['dimensionality-reduction', 'machine-learning', 'topological-data-analysis', 'umap', 'visualization'] | ['dimensionality-reduction', 'machine-learning', 'topological-data-analysis', 'umap', 'visualization'] | 2024-01-08 | [('geomstats/geomstats', 0.5977250933647156, 'math', 1)] | 128 | 7 | null | 1.29 | 30 | 8 | 80 | 0 | 2 | 4 | 2 | 30 | 36 | 90 | 1.2 | 54 |
194 | util | https://github.com/pycqa/isort | ['code-quality'] | null | [] | [] | null | null | null | pycqa/isort | isort | 6,190 | 604 | 48 | Python | https://pycqa.github.io/isort/ | A Python utility / library to sort imports. | pycqa | 2024-01-14 | 2013-09-02 | 543 | 11.396633 | https://avatars.githubusercontent.com/u/8749848?v=4 | A Python utility / library to sort imports. | ['auto-formatter', 'cleaner', 'cli', 'formatter', 'isort', 'linter', 'python-utility', 'sorting-imports'] | ['auto-formatter', 'cleaner', 'cli', 'code-quality', 'formatter', 'isort', 'linter', 'python-utility', 'sorting-imports'] | 2024-01-12 | [('hadialqattan/pycln', 0.6549221277236938, 'util', 0), ('google/yapf', 0.5961623191833496, 'util', 2), ('asottile/reorder-python-imports', 0.5951371192932129, 'util', 2), ('landscapeio/prospector', 0.574863851070404, 'util', 0), ('sethmmorton/natsort', 0.5276709794998169, 'util', 0), ('google/pytype', 0.51016390323638... | 294 | 7 | null | 1.38 | 53 | 33 | 126 | 0 | 5 | 14 | 5 | 53 | 75 | 90 | 1.4 | 54 |
741 | study | https://github.com/zhanymkanov/fastapi-best-practices | [] | null | [] | [] | null | null | null | zhanymkanov/fastapi-best-practices | fastapi-best-practices | 5,917 | 449 | 91 | null | null | FastAPI Best Practices and Conventions we used at our startup | zhanymkanov | 2024-01-14 | 2022-08-09 | 77 | 76.844156 | null | FastAPI Best Practices and Conventions we used at our startup | ['best-practices', 'fastapi'] | ['best-practices', 'fastapi'] | 2023-10-22 | [('fastapi-users/fastapi-users', 0.6014936566352844, 'web', 1), ('asacristani/fastapi-rocket-boilerplate', 0.5217467546463013, 'template', 1), ('dmontagu/fastapi_client', 0.5196253061294556, 'web', 0), ('tiangolo/fastapi', 0.5182605981826782, 'web', 1)] | 10 | 5 | null | 0.21 | 5 | 2 | 17 | 3 | 0 | 0 | 0 | 5 | 11 | 90 | 2.2 | 54 |
369 | time-series | https://github.com/facebookresearch/kats | ['time-series'] | null | [] | [] | null | null | null | facebookresearch/kats | Kats | 4,647 | 508 | 77 | Python | null | Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends. | facebookresearch | 2024-01-14 | 2021-02-25 | 152 | 30.429373 | https://avatars.githubusercontent.com/u/16943930?v=4 | Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends. | [] | ['time-series'] | 2024-01-10 | [('sktime/sktime', 0.5305997729301453, 'time-series', 1), ('alkaline-ml/pmdarima', 0.5154160261154175, 'time-series', 1), ('salesforce/merlion', 0.5117724537849426, 'time-series', 1)] | 136 | 4 | null | 1.75 | 8 | 4 | 35 | 0 | 0 | 1 | 1 | 8 | 12 | 90 | 1.5 | 54 |
380 | ml-ops | https://github.com/aimhubio/aim | [] | null | [] | [] | null | null | null | aimhubio/aim | aim | 4,468 | 274 | 45 | Python | https://aimstack.io | Aim 💫 — An easy-to-use & supercharged open-source experiment tracker. | aimhubio | 2024-01-13 | 2019-05-31 | 243 | 18.343695 | https://avatars.githubusercontent.com/u/51399196?v=4 | Aim 💫 — An easy-to-use & supercharged open-source experiment tracker. | ['ai', 'data-science', 'data-visualization', 'experiment-tracking', 'machine-learning', 'metadata', 'metadata-tracking', 'ml', 'mlflow', 'mlops', 'prompt-engineering', 'pytorch', 'tensorboard', 'tensorflow', 'visualization'] | ['ai', 'data-science', 'data-visualization', 'experiment-tracking', 'machine-learning', 'metadata', 'metadata-tracking', 'ml', 'mlflow', 'mlops', 'prompt-engineering', 'pytorch', 'tensorboard', 'tensorflow', 'visualization'] | 2024-01-12 | [('wandb/client', 0.696733832359314, 'ml', 5), ('polyaxon/datatile', 0.6386370062828064, 'pandas', 5), ('determined-ai/determined', 0.614514172077179, 'ml-ops', 5), ('netflix/metaflow', 0.5948770046234131, 'ml-ops', 5), ('mlflow/mlflow', 0.5842969417572021, 'ml-ops', 4), ('iterative/dvc', 0.5769718885421753, 'ml-ops', ... | 58 | 4 | null | 2.5 | 79 | 29 | 56 | 0 | 9 | 36 | 9 | 79 | 91 | 90 | 1.2 | 54 |
1,552 | study | https://github.com/neetcode-gh/leetcode | ['interview-questions', 'data-structures', 'leetcode'] | Leetcode solutions for NeetCode.io | [] | [] | null | null | null | neetcode-gh/leetcode | leetcode | 4,459 | 2,046 | 40 | JavaScript | null | Leetcode solutions | neetcode-gh | 2024-01-14 | 2021-01-20 | 157 | 28.247059 | null | Leetcode solutions | [] | ['data-structures', 'interview-questions', 'leetcode'] | 2024-01-13 | [('mdmzfzl/neetcode-solutions', 0.6274089217185974, 'study', 3)] | 612 | 1 | null | 34.92 | 182 | 100 | 36 | 0 | 0 | 0 | 0 | 181 | 51 | 90 | 0.3 | 54 |
353 | ml-interpretability | https://github.com/pytorch/captum | [] | null | [] | [] | null | null | null | pytorch/captum | captum | 4,372 | 469 | 225 | Python | https://captum.ai | Model interpretability and understanding for PyTorch | pytorch | 2024-01-14 | 2019-08-27 | 231 | 18.926407 | https://avatars.githubusercontent.com/u/21003710?v=4 | Model interpretability and understanding for PyTorch | ['feature-attribution', 'feature-importance', 'interpretability', 'interpretable-ai', 'interpretable-ml'] | ['feature-attribution', 'feature-importance', 'interpretability', 'interpretable-ai', 'interpretable-ml'] | 2024-01-08 | [('pytorch/ignite', 0.6821672916412354, 'ml-dl', 0), ('tensorflow/lucid', 0.6784272193908691, 'ml-interpretability', 1), ('csinva/imodels', 0.6309248208999634, 'ml', 1), ('skorch-dev/skorch', 0.6131489276885986, 'ml-dl', 0), ('interpretml/interpret', 0.6127338409423828, 'ml-interpretability', 3), ('mrdbourke/pytorch-de... | 104 | 3 | null | 1 | 61 | 40 | 53 | 0 | 1 | 2 | 1 | 61 | 181 | 90 | 3 | 54 |
604 | testing | https://github.com/seleniumbase/seleniumbase | [] | null | [] | [] | null | null | null | seleniumbase/seleniumbase | SeleniumBase | 3,859 | 871 | 125 | Python | https://seleniumbase.io | Browser automation framework for testing with Selenium, Python, and pytest. Includes a Dashboard, a Recorder for generating tests, Undetected Mode, and more. | seleniumbase | 2024-01-13 | 2014-03-04 | 517 | 7.464217 | https://avatars.githubusercontent.com/u/17287301?v=4 | Browser automation framework for testing with Selenium, Python, and pytest. Includes a Dashboard, a Recorder for generating tests, Undetected Mode, and more. | ['behave', 'chrome', 'chromedriver', 'e2e-testing', 'firefox', 'pytest', 'pytest-plugin', 'selenium', 'selenium-python', 'seleniumbase', 'test', 'unittests', 'web-automation', 'webdriver', 'webkit'] | ['behave', 'chrome', 'chromedriver', 'e2e-testing', 'firefox', 'pytest', 'pytest-plugin', 'selenium', 'selenium-python', 'seleniumbase', 'test', 'unittests', 'web-automation', 'webdriver', 'webkit'] | 2024-01-04 | [('cobrateam/splinter', 0.7703961730003357, 'testing', 2), ('microsoft/playwright-python', 0.6941218972206116, 'testing', 2), ('webpy/webpy', 0.5600611567497253, 'web', 0), ('taverntesting/tavern', 0.5573855042457581, 'testing', 1), ('bokeh/bokeh', 0.5535537004470825, 'viz', 0), ('masoniteframework/masonite', 0.5500764... | 37 | 5 | null | 16.27 | 167 | 160 | 120 | 0 | 130 | 91 | 130 | 167 | 348 | 90 | 2.1 | 54 |
1,212 | ml | https://github.com/sanchit-gandhi/whisper-jax | [] | null | [] | [] | null | null | null | sanchit-gandhi/whisper-jax | whisper-jax | 3,813 | 322 | 39 | Jupyter Notebook | null | JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU. | sanchit-gandhi | 2024-01-13 | 2023-03-02 | 47 | 79.913174 | null | JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU. | ['deep-learning', 'jax', 'speech-recognition', 'speech-to-text', 'whisper'] | ['deep-learning', 'jax', 'speech-recognition', 'speech-to-text', 'whisper'] | 2023-12-15 | [('ggerganov/whisper.cpp', 0.6906029582023621, 'util', 3), ('deepmind/dm-haiku', 0.6133875846862793, 'ml-dl', 2), ('m-bain/whisperx', 0.5212621688842773, 'nlp', 3)] | 4 | 2 | null | 2.44 | 44 | 17 | 11 | 1 | 0 | 0 | 0 | 44 | 62 | 90 | 1.4 | 54 |
284 | crypto | https://github.com/ethereum/consensus-specs | [] | null | [] | [] | null | null | null | ethereum/consensus-specs | consensus-specs | 3,329 | 977 | 246 | Python | null | Ethereum Proof-of-Stake Consensus Specifications | ethereum | 2024-01-12 | 2018-09-20 | 279 | 11.90143 | https://avatars.githubusercontent.com/u/6250754?v=4 | Ethereum Proof-of-Stake Consensus Specifications | [] | [] | 2024-01-11 | [] | 148 | 3 | null | 10.83 | 251 | 107 | 65 | 0 | 16 | 16 | 16 | 251 | 225 | 90 | 0.9 | 54 |
1,759 | data | https://github.com/rom1504/img2dataset | [] | null | [] | [] | null | null | null | rom1504/img2dataset | img2dataset | 2,953 | 288 | 29 | Python | null | Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine. | rom1504 | 2024-01-13 | 2021-08-11 | 128 | 22.916851 | null | Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine. | ['big-data', 'dataset', 'deep-learning', 'download-images', 'image', 'image-dataset', 'multimodal'] | ['big-data', 'dataset', 'deep-learning', 'download-images', 'image', 'image-dataset', 'multimodal'] | 2024-01-13 | [('fourthbrain/fastapi-for-machine-learning-live-demo', 0.5232915878295898, 'web', 0), ('aiqc/aiqc', 0.5084776282310486, 'ml-ops', 0), ('microsoft/deepspeed', 0.5075109601020813, 'ml-dl', 1)] | 32 | 5 | null | 0.54 | 48 | 29 | 30 | 0 | 4 | 35 | 4 | 48 | 95 | 90 | 2 | 54 |
1,359 | llm | https://github.com/iryna-kondr/scikit-llm | [] | null | [] | [] | null | null | null | iryna-kondr/scikit-llm | scikit-llm | 2,820 | 226 | 36 | Python | https://beastbyte.ai/ | Seamlessly integrate LLMs into scikit-learn. | iryna-kondr | 2024-01-12 | 2023-05-12 | 37 | 75.057034 | null | Seamlessly integrate LLMs into scikit-learn. | ['chatgpt', 'deep-learning', 'llm', 'machine-learning', 'scikit-learn', 'transformers'] | ['chatgpt', 'deep-learning', 'llm', 'machine-learning', 'scikit-learn', 'transformers'] | 2023-12-25 | [('microsoft/jarvis', 0.6588683128356934, 'llm', 1), ('alpha-vllm/llama2-accessory', 0.6441587209701538, 'llm', 0), ('tigerlab-ai/tiger', 0.6261765956878662, 'llm', 1), ('koaning/scikit-lego', 0.614821195602417, 'ml', 2), ('vllm-project/vllm', 0.6003293395042419, 'llm', 1), ('microsoft/semantic-kernel', 0.5926992893218... | 9 | 1 | null | 1.77 | 10 | 6 | 8 | 1 | 14 | 24 | 14 | 10 | 12 | 90 | 1.2 | 54 |
1,429 | ml-dl | https://github.com/cvg/lightglue | [] | null | [] | [] | null | null | null | cvg/lightglue | LightGlue | 2,664 | 259 | 46 | Python | null | LightGlue: Local Feature Matching at Light Speed (ICCV 2023) | cvg | 2024-01-13 | 2023-06-25 | 31 | 85.150685 | https://avatars.githubusercontent.com/u/840224?v=4 | LightGlue: Local Feature Matching at Light Speed (ICCV 2023) | ['deep-learning', 'image-matching', 'pose-estimation', 'transformers'] | ['deep-learning', 'image-matching', 'pose-estimation', 'transformers'] | 2023-11-21 | [('facebookresearch/detr', 0.5226452350616455, 'ml-dl', 0)] | 6 | 2 | null | 0.5 | 35 | 7 | 7 | 2 | 1 | 2 | 1 | 35 | 65 | 90 | 1.9 | 54 |
1,792 | perf | https://github.com/airtai/faststream | [] | null | [] | [] | null | null | null | airtai/faststream | faststream | 1,435 | 53 | 12 | Python | https://faststream.airt.ai/latest/ | FastStream is a powerful and easy-to-use Python framework for building asynchronous services interacting with event streams such as Apache Kafka, RabbitMQ, NATS and Redis. | airtai | 2024-01-13 | 2022-12-01 | 60 | 23.635294 | https://avatars.githubusercontent.com/u/84014356?v=4 | FastStream is a powerful and easy-to-use Python framework for building asynchronous services interacting with event streams such as Apache Kafka, RabbitMQ, NATS and Redis. | ['asyncapi', 'asyncio', 'distributed-systems', 'fastkafka', 'faststream', 'kafka', 'nats', 'propan', 'rabbitmq', 'redis', 'stream-processing'] | ['asyncapi', 'asyncio', 'distributed-systems', 'fastkafka', 'faststream', 'kafka', 'nats', 'propan', 'rabbitmq', 'redis', 'stream-processing'] | 2024-01-13 | [('pathwaycom/pathway', 0.6327610611915588, 'data', 1), ('samuelcolvin/arq', 0.6273122429847717, 'data', 2), ('python-trio/trio', 0.6224059462547302, 'perf', 0), ('magicstack/uvloop', 0.6053869128227234, 'util', 1), ('agronholm/anyio', 0.5833213329315186, 'perf', 1), ('miguelgrinberg/python-socketio', 0.577484846115112... | 23 | 2 | null | 12.35 | 309 | 283 | 14 | 0 | 37 | 33 | 37 | 307 | 249 | 90 | 0.8 | 54 |
1,675 | study | https://github.com/realpython/python-guide | [] | null | [] | [] | null | null | null | realpython/python-guide | python-guide | 27,160 | 5,988 | 1,384 | Batchfile | https://docs.python-guide.org | Python best practices guidebook, written for humans. | realpython | 2024-01-13 | 2011-03-15 | 672 | 40.416667 | https://avatars.githubusercontent.com/u/5448020?v=4 | Python best practices guidebook, written for humans. | ['book', 'guide', 'kennethreitz'] | ['book', 'guide', 'kennethreitz'] | 2023-06-13 | [('amaargiru/pyroad', 0.6154986023902893, 'study', 0), ('wesm/pydata-book', 0.5613322854042053, 'study', 0), ('eleutherai/pyfra', 0.5539833307266235, 'ml', 0), ('brandon-rhodes/python-patterns', 0.5476312637329102, 'util', 0), ('jakevdp/pythondatasciencehandbook', 0.5322774648666382, 'study', 0), ('mynameisfiber/high_p... | 474 | 6 | null | 0 | 5 | 1 | 156 | 7 | 0 | 0 | 0 | 5 | 5 | 90 | 1 | 53 |
683 | ml-dl | https://github.com/matterport/mask_rcnn | [] | null | [] | [] | null | null | null | matterport/mask_rcnn | Mask_RCNN | 23,803 | 11,620 | 587 | Python | null | Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow | matterport | 2024-01-14 | 2017-10-19 | 327 | 72.633391 | https://avatars.githubusercontent.com/u/4206481?v=4 | Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow | ['instance-segmentation', 'keras', 'mask-rcnn', 'object-detection', 'tensorflow'] | ['instance-segmentation', 'keras', 'mask-rcnn', 'object-detection', 'tensorflow'] | 2019-03-31 | [('open-mmlab/mmdetection', 0.5989094376564026, 'ml', 3), ('roboflow/notebooks', 0.5560668706893921, 'study', 1), ('nyandwi/modernconvnets', 0.5529733300209045, 'ml-dl', 2), ('blakeblackshear/frigate', 0.5429755449295044, 'util', 2), ('facebookresearch/segment-anything', 0.5424768328666687, 'ml-dl', 2), ('deci-ai/super... | 47 | 6 | null | 0 | 49 | 12 | 76 | 59 | 0 | 0 | 0 | 49 | 51 | 90 | 1 | 53 |
643 | util | https://github.com/keon/algorithms | [] | null | [] | [] | null | null | null | keon/algorithms | algorithms | 23,270 | 4,629 | 635 | Python | null | Minimal examples of data structures and algorithms in Python | keon | 2024-01-13 | 2016-11-17 | 375 | 61.935361 | null | Minimal examples of data structures and algorithms in Python | ['algorithm', 'algorithms', 'competitive-programming', 'data-structure', 'graph', 'search', 'sort', 'tree'] | ['algorithm', 'algorithms', 'competitive-programming', 'data-structure', 'graph', 'search', 'sort', 'tree'] | 2023-04-04 | [('thealgorithms/python', 0.707886815071106, 'study', 1), ('joowani/binarytree', 0.6219033002853394, 'util', 2), ('python-odin/odin', 0.6064568161964417, 'util', 0), ('pandas-dev/pandas', 0.6043705940246582, 'pandas', 0), ('pyomo/pyomo', 0.5572477579116821, 'math', 0), ('krzjoa/awesome-python-data-science', 0.551280081... | 198 | 4 | null | 0.12 | 10 | 1 | 87 | 10 | 0 | 0 | 0 | 10 | 6 | 90 | 0.6 | 53 |
105 | nlp | https://github.com/rare-technologies/gensim | [] | null | [] | [] | null | null | null | rare-technologies/gensim | gensim | 14,914 | 4,381 | 433 | Python | https://radimrehurek.com/gensim | Topic Modelling for Humans | rare-technologies | 2024-01-14 | 2011-02-10 | 676 | 22.038843 | null | Topic Modelling for Humans | ['data-mining', 'data-science', 'document-similarity', 'fasttext', 'gensim', 'information-retrieval', 'machine-learning', 'natural-language-processing', 'neural-network', 'nlp', 'topic-modeling', 'word-embeddings', 'word-similarity', 'word2vec'] | ['data-mining', 'data-science', 'document-similarity', 'fasttext', 'gensim', 'information-retrieval', 'machine-learning', 'natural-language-processing', 'neural-network', 'nlp', 'topic-modeling', 'word-embeddings', 'word-similarity', 'word2vec'] | 2023-10-01 | [('ddangelov/top2vec', 0.59908527135849, 'nlp', 2), ('maartengr/bertopic', 0.5905485153198242, 'nlp', 3), ('brettkromkamp/topic-db', 0.539949893951416, 'data', 0), ('ddbourgin/numpy-ml', 0.5375690460205078, 'ml', 3), ('sebischair/lbl2vec', 0.5351875424385071, 'nlp', 4), ('sloria/textblob', 0.5176156759262085, 'nlp', 2)... | 449 | 6 | null | 1.42 | 20 | 3 | 157 | 4 | 1 | 6 | 1 | 20 | 25 | 90 | 1.2 | 53 |
1,884 | util | https://github.com/ninja-build/ninja | ['build'] | Ninja is a small build system with a focus on speed. | [] | [] | null | null | null | ninja-build/ninja | ninja | 10,184 | 1,544 | 264 | C++ | https://ninja-build.org/ | a small build system with a focus on speed | ninja-build | 2024-01-14 | 2011-02-06 | 677 | 15.03649 | https://avatars.githubusercontent.com/u/11653218?v=4 | a small build system with a focus on speed | [] | ['build'] | 2024-01-02 | [('scikit-build/scikit-build', 0.562438428401947, 'ml', 0)] | 285 | 4 | null | 0.73 | 76 | 42 | 157 | 0 | 0 | 2 | 2 | 76 | 107 | 90 | 1.4 | 53 |
133 | ml | https://github.com/epistasislab/tpot | [] | null | [] | [] | null | null | null | epistasislab/tpot | tpot | 9,381 | 1,552 | 290 | Python | http://epistasislab.github.io/tpot/ | A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. | epistasislab | 2024-01-13 | 2015-11-03 | 430 | 21.816279 | https://avatars.githubusercontent.com/u/20861190?v=4 | A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. | ['adsp', 'ag066833', 'aiml', 'alzheimer', 'alzheimers', 'automated-machine-learning', 'automation', 'automl', 'data-science', 'feature-engineering', 'gradient-boosting', 'hyperparameter-optimization', 'machine-learning', 'model-selection', 'nia', 'parameter-tuning', 'random-forest', 'scikit-learn', 'u01ag066833'] | ['adsp', 'ag066833', 'aiml', 'alzheimer', 'alzheimers', 'automated-machine-learning', 'automation', 'automl', 'data-science', 'feature-engineering', 'gradient-boosting', 'hyperparameter-optimization', 'machine-learning', 'model-selection', 'nia', 'parameter-tuning', 'random-forest', 'scikit-learn', 'u01ag066833'] | 2023-12-08 | [('automl/auto-sklearn', 0.6574358940124512, 'ml', 4), ('featurelabs/featuretools', 0.6507097482681274, 'ml', 6), ('microsoft/nni', 0.6485167741775513, 'ml', 6), ('google/pyglove', 0.6232022643089294, 'util', 2), ('scikit-learn/scikit-learn', 0.6184797286987305, 'ml', 2), ('mljar/mljar-supervised', 0.6145864129066467, ... | 118 | 8 | null | 0.4 | 14 | 6 | 100 | 1 | 2 | 4 | 2 | 14 | 16 | 90 | 1.1 | 53 |
397 | web | https://github.com/falconry/falcon | [] | null | [] | [] | null | null | null | falconry/falcon | falcon | 9,306 | 926 | 262 | Python | https://falcon.readthedocs.io/en/stable/ | The no-magic web data plane API and microservices framework for Python developers, with a focus on reliability, correctness, and performance at scale. | falconry | 2024-01-12 | 2012-12-06 | 581 | 15.997544 | https://avatars.githubusercontent.com/u/11353642?v=4 | The no-magic web data plane API and microservices framework for Python developers, with a focus on reliability, correctness, and performance at scale. | ['api', 'api-rest', 'asgi', 'framework', 'http', 'microservices', 'rest', 'web', 'wsgi'] | ['api', 'api-rest', 'asgi', 'framework', 'http', 'microservices', 'rest', 'web', 'wsgi'] | 2023-12-26 | [('pallets/flask', 0.7083405256271362, 'web', 1), ('neoteroi/blacksheep', 0.6875892877578735, 'web', 4), ('pallets/quart', 0.6842796206474304, 'web', 1), ('starlite-api/starlite', 0.6774393916130066, 'web', 3), ('bottlepy/bottle', 0.677134096622467, 'web', 2), ('encode/uvicorn', 0.6588360667228699, 'web', 2), ('klen/mu... | 201 | 4 | null | 0.42 | 43 | 24 | 135 | 1 | 6 | 7 | 6 | 43 | 59 | 90 | 1.4 | 53 |
293 | util | https://github.com/paramiko/paramiko | [] | null | [] | [] | null | null | null | paramiko/paramiko | paramiko | 8,659 | 2,010 | 316 | Python | http://paramiko.org | The leading native Python SSHv2 protocol library. | paramiko | 2024-01-14 | 2009-02-02 | 782 | 11.070868 | https://avatars.githubusercontent.com/u/1108455?v=4 | The leading native Python SSHv2 protocol library. | [] | [] | 2023-12-18 | [('pypy/pypy', 0.6160950064659119, 'util', 0), ('pyston/pyston', 0.5798661708831787, 'util', 0), ('secdev/scapy', 0.5442431569099426, 'util', 0), ('legrandin/pycryptodome', 0.5410947203636169, 'util', 0), ('pytoolz/toolz', 0.5407304763793945, 'util', 0), ('1200wd/bitcoinlib', 0.5394938588142395, 'crypto', 0), ('ethereu... | 187 | 5 | null | 2.58 | 65 | 15 | 182 | 1 | 0 | 12 | 12 | 65 | 111 | 90 | 1.7 | 53 |
1,433 | ml-dl | https://github.com/nvidia/apex | [] | null | [] | [] | null | null | null | nvidia/apex | apex | 7,797 | 1,306 | 102 | Python | null | A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch | nvidia | 2024-01-14 | 2018-04-23 | 301 | 25.891366 | https://avatars.githubusercontent.com/u/1728152?v=4 | A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch | [] | [] | 2024-01-12 | [('pytorch/ignite', 0.76711106300354, 'ml-dl', 0), ('huggingface/accelerate', 0.7648141980171204, 'ml', 0), ('intel/intel-extension-for-pytorch', 0.7110769152641296, 'perf', 0), ('skorch-dev/skorch', 0.6882312893867493, 'ml-dl', 0), ('pytorch/data', 0.6665452122688293, 'data', 0), ('laekov/fastmoe', 0.6603500247001648,... | 125 | 2 | null | 1.65 | 70 | 35 | 70 | 0 | 0 | 1 | 1 | 70 | 87 | 90 | 1.2 | 53 |
388 | data | https://github.com/yzhao062/pyod | [] | null | [] | [] | null | null | null | yzhao062/pyod | pyod | 7,738 | 1,307 | 148 | Python | http://pyod.readthedocs.io | A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection) | yzhao062 | 2024-01-13 | 2017-10-03 | 330 | 23.448485 | null | A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection) | ['anomaly', 'anomaly-detection', 'autoencoder', 'data-analysis', 'data-mining', 'data-science', 'deep-learning', 'fraud-detection', 'machine-learning', 'neural-networks', 'novelty-detection', 'out-of-distribution-detection', 'outlier-detection', 'outlier-ensembles', 'outliers', 'unsupervised-learning'] | ['anomaly', 'anomaly-detection', 'autoencoder', 'data-analysis', 'data-mining', 'data-science', 'deep-learning', 'fraud-detection', 'machine-learning', 'neural-networks', 'novelty-detection', 'out-of-distribution-detection', 'outlier-detection', 'outlier-ensembles', 'outliers', 'unsupervised-learning'] | 2023-12-16 | [('pycaret/pycaret', 0.7633078694343567, 'ml', 3), ('unit8co/darts', 0.7557379603385925, 'time-series', 4), ('aistream-peelout/flow-forecast', 0.6631090044975281, 'time-series', 2), ('tdameritrade/stumpy', 0.6203436255455017, 'time-series', 2), ('rasbt/mlxtend', 0.6038527488708496, 'ml', 4), ('scikit-learn-contrib/imba... | 50 | 5 | null | 0.83 | 21 | 9 | 76 | 1 | 4 | 6 | 4 | 21 | 25 | 90 | 1.2 | 53 |
1,257 | llm | https://github.com/openlm-research/open_llama | ['llama', 'language-model'] | OpenLLaMA: An Open Reproduction of LLaMA | ['2302.13971'] | [] | null | null | null | openlm-research/open_llama | open_llama | 7,006 | 362 | 115 | null | null | OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset | openlm-research | 2024-01-13 | 2023-04-28 | 39 | 177.046931 | https://avatars.githubusercontent.com/u/132110378?v=4 | OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset | [] | ['language-model', 'llama'] | 2023-07-16 | [('microsoft/llama-2-onnx', 0.6107590794563293, 'llm', 2), ('jzhang38/tinyllama', 0.5819482207298279, 'llm', 2), ('facebookresearch/llama', 0.5816770195960999, 'llm', 2), ('togethercomputer/redpajama-data', 0.5621833801269531, 'llm', 0), ('lm-sys/fastchat', 0.5599814653396606, 'llm', 1), ('karpathy/llama2.c', 0.5405749... | 3 | 3 | null | 0.35 | 8 | 3 | 9 | 6 | 0 | 0 | 0 | 8 | 3 | 90 | 0.4 | 53 |
69 | gamedev | https://github.com/pygame/pygame | [] | null | [] | [] | 1 | null | null | pygame/pygame | pygame | 6,667 | 2,977 | 160 | C | https://www.pygame.org | 🐍🎮 pygame (the library) is a Free and Open Source python programming language library for making multimedia applications like games built on top of the excellent SDL library. C, Python, Native, OpenGL. | pygame | 2024-01-14 | 2017-03-26 | 357 | 18.660136 | https://avatars.githubusercontent.com/u/20628127?v=4 | 🐍🎮 pygame (the library) is a Free and Open Source python programming language library for making multimedia applications like games built on top of the excellent SDL library. C, Python, Native, OpenGL. | ['game-dev', 'game-development', 'gamedev', 'pygame', 'sdl', 'sdl2'] | ['game-dev', 'game-development', 'gamedev', 'pygame', 'sdl', 'sdl2'] | 2023-12-30 | [('pyglet/pyglet', 0.717469334602356, 'gamedev', 1), ('renpy/pygame_sdl2', 0.7130681872367859, 'gamedev', 2), ('lordmauve/pgzero', 0.6985493302345276, 'gamedev', 1), ('pygamelib/pygamelib', 0.6512402892112732, 'gamedev', 2), ('pythonarcade/arcade', 0.6259638071060181, 'gamedev', 0), ('panda3d/panda3d', 0.60982692241668... | 315 | 0 | null | 9.33 | 125 | 37 | 83 | 0 | 11 | 13 | 11 | 125 | 134 | 90 | 1.1 | 53 |
74 | gis | https://github.com/python-visualization/folium | [] | null | [] | [] | null | null | null | python-visualization/folium | folium | 6,539 | 2,245 | 167 | Python | https://python-visualization.github.io/folium/ | Python Data. Leaflet.js Maps. | python-visualization | 2024-01-13 | 2013-05-09 | 559 | 11.682746 | https://avatars.githubusercontent.com/u/9969242?v=4 | Python Data. Leaflet.js Maps. | ['data-science', 'data-visualization', 'javascript', 'maps'] | ['data-science', 'data-visualization', 'javascript', 'maps'] | 2024-01-02 | [('jupyter-widgets/ipyleaflet', 0.6334434151649475, 'gis', 0), ('bokeh/bokeh', 0.5900196433067322, 'viz', 1), ('plotly/dash', 0.5898042321205139, 'viz', 2), ('giswqs/mapwidget', 0.5697619915008545, 'gis', 0), ('giswqs/geemap', 0.5445337295532227, 'gis', 1), ('raphaelquast/eomaps', 0.5424359440803528, 'gis', 0), ('openg... | 159 | 5 | null | 2 | 57 | 41 | 130 | 0 | 2 | 2 | 2 | 57 | 114 | 90 | 2 | 53 |
793 | web | https://github.com/pallets/werkzeug | [] | null | [] | [] | null | null | null | pallets/werkzeug | werkzeug | 6,480 | 1,729 | 221 | Python | https://werkzeug.palletsprojects.com | The comprehensive WSGI web application library. | pallets | 2024-01-13 | 2010-10-18 | 693 | 9.348722 | https://avatars.githubusercontent.com/u/16748505?v=4 | The comprehensive WSGI web application library. | ['http', 'pallets', 'werkzeug', 'wsgi'] | ['http', 'pallets', 'werkzeug', 'wsgi'] | 2024-01-01 | [('pallets/flask', 0.7842201590538025, 'web', 3), ('pylons/pyramid', 0.7471210360527039, 'web', 1), ('bottlepy/bottle', 0.6876417994499207, 'web', 1), ('benoitc/gunicorn', 0.6659462451934814, 'web', 2), ('masoniteframework/masonite', 0.6412118673324585, 'web', 0), ('falconry/falcon', 0.630772590637207, 'web', 2), ('pyl... | 486 | 5 | null | 4.12 | 47 | 33 | 161 | 0 | 12 | 7 | 12 | 47 | 41 | 90 | 0.9 | 53 |
1,640 | llm | https://github.com/nat/openplayground | ['language-model', 'local'] | null | [] | [] | null | null | null | nat/openplayground | openplayground | 5,904 | 441 | 58 | TypeScript | null | An LLM playground you can run on your laptop | nat | 2024-01-14 | 2023-02-26 | 48 | 122.272189 | null | An LLM playground you can run on your laptop | [] | ['language-model', 'local'] | 2023-06-05 | [('eugeneyan/open-llms', 0.6209505796432495, 'study', 0), ('alphasecio/langchain-examples', 0.6207661628723145, 'llm', 0), ('hwchase17/langchain', 0.607382595539093, 'llm', 1), ('young-geng/easylm', 0.593249499797821, 'llm', 1), ('thudm/chatglm2-6b', 0.5894226431846619, 'llm', 0), ('mlc-ai/web-llm', 0.589094340801239, ... | 16 | 3 | null | 0.67 | 11 | 2 | 11 | 7 | 0 | 0 | 0 | 11 | 5 | 90 | 0.5 | 53 |
182 | security | https://github.com/pycqa/bandit | ['code-quality'] | null | [] | [] | null | null | null | pycqa/bandit | bandit | 5,722 | 569 | 66 | Python | https://bandit.readthedocs.io | Bandit is a tool designed to find common security issues in Python code. | pycqa | 2024-01-13 | 2018-04-26 | 300 | 19.028029 | https://avatars.githubusercontent.com/u/8749848?v=4 | Bandit is a tool designed to find common security issues in Python code. | ['bandit', 'linter', 'security', 'security-scanner', 'security-tools', 'static-code-analysis'] | ['bandit', 'code-quality', 'linter', 'security', 'security-scanner', 'security-tools', 'static-code-analysis'] | 2024-01-13 | [('aswinnnn/pyscan', 0.5267046093940735, 'security', 3), ('nedbat/coveragepy', 0.5142317414283752, 'testing', 0)] | 175 | 5 | null | 0.87 | 48 | 29 | 70 | 0 | 2 | 7 | 2 | 48 | 49 | 90 | 1 | 53 |
1,354 | util | https://github.com/icloud-photos-downloader/icloud_photos_downloader | ['photos-export', 'library-photos'] | null | [] | [] | null | null | null | icloud-photos-downloader/icloud_photos_downloader | icloud_photos_downloader | 5,476 | 506 | 100 | Python | null | A command-line tool to download photos from iCloud | icloud-photos-downloader | 2024-01-14 | 2016-05-13 | 402 | 13.602555 | https://avatars.githubusercontent.com/u/73247967?v=4 | A command-line tool to download photos from iCloud | [] | ['library-photos', 'photos-export'] | 2024-01-05 | [] | 36 | 2 | null | 2.23 | 97 | 57 | 93 | 0 | 28 | 4 | 28 | 96 | 244 | 90 | 2.5 | 53 |
510 | util | https://github.com/agronholm/apscheduler | [] | null | [] | [] | null | null | null | agronholm/apscheduler | apscheduler | 5,463 | 698 | 128 | Python | null | Task scheduling library for Python | agronholm | 2024-01-14 | 2016-03-27 | 409 | 13.347644 | null | Task scheduling library for Python | [] | [] | 2024-01-11 | [('dbader/schedule', 0.7123571634292603, 'util', 0), ('dask/dask', 0.6700900197029114, 'perf', 0), ('pyinvoke/invoke', 0.6340285539627075, 'util', 0), ('pypy/pypy', 0.6140989065170288, 'util', 0), ('pytoolz/toolz', 0.6112861037254333, 'util', 0), ('bogdanp/dramatiq', 0.6053295135498047, 'util', 0), ('dask/distributed',... | 44 | 3 | null | 2.81 | 48 | 27 | 95 | 0 | 2 | 8 | 2 | 48 | 184 | 90 | 3.8 | 53 |
561 | gis | https://github.com/gboeing/osmnx | [] | null | [] | [] | null | null | null | gboeing/osmnx | osmnx | 4,514 | 805 | 116 | Python | https://osmnx.readthedocs.io | OSMnx is a Python package to easily download, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap. | gboeing | 2024-01-13 | 2016-07-24 | 392 | 11.506919 | null | OSMnx is a Python package to easily download, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap. | ['geography', 'geospatial', 'gis', 'mapping', 'networks', 'networkx', 'openstreetmap', 'osm', 'osmnx', 'overpass-api', 'routing', 'spatial', 'spatial-analysis', 'spatial-data', 'street-networks', 'transport', 'transportation', 'urban', 'urban-planning'] | ['geography', 'geospatial', 'gis', 'mapping', 'networks', 'networkx', 'openstreetmap', 'osm', 'osmnx', 'overpass-api', 'routing', 'spatial', 'spatial-analysis', 'spatial-data', 'street-networks', 'transport', 'transportation', 'urban', 'urban-planning'] | 2024-01-12 | [('gboeing/osmnx-examples', 0.7930247187614441, 'gis', 5), ('marceloprates/prettymaps', 0.6797459125518799, 'viz', 1), ('gboeing/street-network-models', 0.5225948691368103, 'sim', 0), ('westhealth/pyvis', 0.5170513987541199, 'graph', 1)] | 83 | 3 | null | 11.06 | 42 | 38 | 91 | 0 | 0 | 8 | 8 | 42 | 68 | 90 | 1.6 | 53 |
727 | ml-dl | https://github.com/pytorch/ignite | [] | null | [] | [] | 1 | null | null | pytorch/ignite | ignite | 4,411 | 611 | 60 | Python | https://pytorch-ignite.ai | High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. | pytorch | 2024-01-13 | 2017-11-23 | 322 | 13.668437 | https://avatars.githubusercontent.com/u/21003710?v=4 | High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. | ['deep-learning', 'machine-learning', 'metrics', 'neural-network', 'pytorch'] | ['deep-learning', 'machine-learning', 'metrics', 'neural-network', 'pytorch'] | 2024-01-11 | [('skorch-dev/skorch', 0.8268391489982605, 'ml-dl', 2), ('mrdbourke/pytorch-deep-learning', 0.7811650037765503, 'study', 3), ('intel/intel-extension-for-pytorch', 0.7741976380348206, 'perf', 4), ('nvidia/apex', 0.76711106300354, 'ml-dl', 0), ('pyg-team/pytorch_geometric', 0.7287918925285339, 'ml-dl', 2), ('rasbt/machin... | 204 | 7 | null | 2.77 | 115 | 105 | 75 | 0 | 3 | 3 | 3 | 115 | 53 | 90 | 0.5 | 53 |
43 | data | https://github.com/lk-geimfari/mimesis | [] | null | [] | [] | null | null | null | lk-geimfari/mimesis | mimesis | 4,144 | 321 | 62 | Python | https://mimesis.name | Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently. | lk-geimfari | 2024-01-14 | 2016-09-09 | 385 | 10.747684 | null | Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently. | ['api-mock', 'data', 'dataframe', 'datascience', 'dummy', 'fake', 'faker', 'fixtures', 'generator', 'json', 'json-generator', 'mimesis', 'mock', 'pandas', 'polars', 'schema', 'syntetic', 'synthetic-data', 'testing'] | ['api-mock', 'data', 'dataframe', 'datascience', 'dummy', 'fake', 'faker', 'fixtures', 'generator', 'json', 'json-generator', 'mimesis', 'mock', 'pandas', 'polars', 'schema', 'syntetic', 'synthetic-data', 'testing'] | 2024-01-12 | [('joke2k/faker', 0.6268561482429504, 'data', 3), ('getsentry/responses', 0.5823182463645935, 'testing', 0), ('python-odin/odin', 0.5751269459724426, 'util', 1), ('pytoolz/toolz', 0.5705004334449768, 'util', 0), ('marshmallow-code/marshmallow', 0.5606078505516052, 'util', 1), ('asacristani/fastapi-rocket-boilerplate', ... | 117 | 4 | null | 4.63 | 51 | 44 | 89 | 0 | 11 | 9 | 11 | 51 | 73 | 90 | 1.4 | 53 |
335 | ml | https://github.com/apple/coremltools | [] | null | [] | [] | null | null | null | apple/coremltools | coremltools | 3,860 | 581 | 116 | Python | https://coremltools.readme.io | Core ML tools contain supporting tools for Core ML model conversion, editing, and validation. | apple | 2024-01-14 | 2017-06-30 | 343 | 11.234927 | https://avatars.githubusercontent.com/u/10639145?v=4 | Core ML tools contain supporting tools for Core ML model conversion, editing, and validation. | ['coreml', 'coremltools', 'machine-learning', 'model-conversion', 'model-converter', 'pytorch', 'tensorflow'] | ['coreml', 'coremltools', 'machine-learning', 'model-conversion', 'model-converter', 'pytorch', 'tensorflow'] | 2024-01-10 | [('huggingface/exporters', 0.6746289730072021, 'ml', 6), ('microsoft/nni', 0.5904099345207214, 'ml', 3), ('huggingface/datasets', 0.5799334049224854, 'nlp', 3), ('polyaxon/polyaxon', 0.5726978778839111, 'ml-ops', 3), ('selfexplainml/piml-toolbox', 0.558883786201477, 'ml-interpretability', 0), ('districtdatalabs/yellowb... | 159 | 3 | null | 2.06 | 127 | 82 | 80 | 0 | 6 | 6 | 6 | 126 | 286 | 90 | 2.3 | 53 |
252 | ml | https://github.com/microsoft/flaml | [] | null | [] | [] | null | null | null | microsoft/flaml | FLAML | 3,493 | 488 | 56 | Jupyter Notebook | https://microsoft.github.io/FLAML/ | A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP. | microsoft | 2024-01-13 | 2020-08-20 | 179 | 19.436407 | https://avatars.githubusercontent.com/u/6154722?v=4 | A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP. | ['automated-machine-learning', 'automl', 'classification', 'data-science', 'deep-learning', 'finetuning', 'hyperparam', 'hyperparameter-optimization', 'jupyter-notebook', 'machine-learning', 'natural-language-generation', 'natural-language-processing', 'random-forest', 'regression', 'scikit-learn', 'tabular-data', 'tim... | ['automated-machine-learning', 'automl', 'classification', 'data-science', 'deep-learning', 'finetuning', 'hyperparam', 'hyperparameter-optimization', 'jupyter-notebook', 'machine-learning', 'natural-language-generation', 'natural-language-processing', 'random-forest', 'regression', 'scikit-learn', 'tabular-data', 'tim... | 2023-11-29 | [('mljar/mljar-supervised', 0.7940219044685364, 'ml', 7), ('microsoft/nni', 0.7865293025970459, 'ml', 6), ('keras-team/autokeras', 0.7519674897193909, 'ml-dl', 4), ('awslabs/autogluon', 0.7324180603027344, 'ml', 9), ('automl/auto-sklearn', 0.7281423807144165, 'ml', 4), ('shankarpandala/lazypredict', 0.6851475834846497,... | 80 | 4 | null | 2.98 | 31 | 13 | 41 | 2 | 18 | 20 | 18 | 31 | 50 | 90 | 1.6 | 53 |
472 | nlp | https://github.com/neuralmagic/deepsparse | [] | null | [] | [] | null | null | null | neuralmagic/deepsparse | deepsparse | 2,707 | 160 | 53 | Python | https://neuralmagic.com/deepsparse/ | Sparsity-aware deep learning inference runtime for CPUs | neuralmagic | 2024-01-13 | 2020-12-14 | 163 | 16.59282 | https://avatars.githubusercontent.com/u/68670575?v=4 | Sparsity-aware deep learning inference runtime for CPUs | ['computer-vision', 'cpus', 'deepsparse', 'inference', 'llm-inference', 'machinelearning', 'nlp', 'object-detection', 'onnx', 'performance', 'pretrained-models', 'pruning', 'quantization', 'sparsification'] | ['computer-vision', 'cpus', 'deepsparse', 'inference', 'llm-inference', 'machinelearning', 'nlp', 'object-detection', 'onnx', 'performance', 'pretrained-models', 'pruning', 'quantization', 'sparsification'] | 2024-01-10 | [('neuralmagic/sparseml', 0.7135436534881592, 'ml-dl', 5), ('microsoft/deepspeed', 0.643064022064209, 'ml-dl', 1), ('microsoft/onnxruntime', 0.6196989417076111, 'ml', 1), ('alpa-projects/alpa', 0.6077420711517334, 'ml-dl', 0), ('lutzroeder/netron', 0.5835353136062622, 'ml', 2), ('huggingface/datasets', 0.57524508237838... | 41 | 3 | null | 8.13 | 222 | 202 | 38 | 0 | 10 | 12 | 10 | 222 | 98 | 90 | 0.4 | 53 |
539 | data | https://github.com/sqlalchemy/alembic | [] | null | [] | [] | null | null | null | sqlalchemy/alembic | alembic | 2,302 | 211 | 19 | Python | null | A database migrations tool for SQLAlchemy. | sqlalchemy | 2024-01-13 | 2018-11-27 | 270 | 8.525926 | https://avatars.githubusercontent.com/u/6043126?v=4 | A database migrations tool for SQLAlchemy. | ['sql', 'sqlalchemy'] | ['sql', 'sqlalchemy'] | 2024-01-13 | [('sqlalchemy/sqlalchemy', 0.8273295164108276, 'data', 2), ('agronholm/sqlacodegen', 0.6634976267814636, 'data', 0), ('mause/duckdb_engine', 0.6483481526374817, 'data', 2), ('tiangolo/sqlmodel', 0.6223205924034119, 'data', 2), ('aminalaee/sqladmin', 0.5552855730056763, 'data', 1), ('ibis-project/ibis', 0.55105251073837... | 181 | 5 | null | 2.63 | 84 | 64 | 62 | 0 | 16 | 24 | 16 | 84 | 228 | 90 | 2.7 | 53 |
1,689 | util | https://github.com/pypa/setuptools | ['setuptools', 'build'] | null | [] | [] | null | null | null | pypa/setuptools | setuptools | 2,224 | 1,095 | 93 | Python | https://pypi.org/project/setuptools/ | Official project repository for the Setuptools build system | pypa | 2024-01-12 | 2016-03-29 | 409 | 5.437653 | https://avatars.githubusercontent.com/u/647025?v=4 | Official project repository for the Setuptools build system | [] | ['build', 'setuptools'] | 2024-01-11 | [('pyo3/setuptools-rust', 0.6672810912132263, 'util', 2)] | 587 | 4 | null | 15.08 | 145 | 71 | 95 | 0 | 28 | 83 | 28 | 146 | 273 | 90 | 1.9 | 53 |
1,898 | pandas | https://github.com/delta-io/delta-rs | ['databricks', 'rust'] | null | [] | [] | null | null | null | delta-io/delta-rs | delta-rs | 1,620 | 305 | 38 | Rust | https://delta-io.github.io/delta-rs/ | A native Rust library for Delta Lake, with bindings into Python | delta-io | 2024-01-16 | 2020-04-26 | 196 | 8.253275 | https://avatars.githubusercontent.com/u/49767398?v=4 | A native Rust library for Delta Lake, with bindings into Python | ['databricks', 'delta', 'delta-lake', 'pandas', 'pandas-dataframe', 'rust'] | ['databricks', 'delta', 'delta-lake', 'pandas', 'pandas-dataframe', 'rust'] | 2024-01-16 | [('eventual-inc/daft', 0.6028104424476624, 'pandas', 1), ('pola-rs/polars', 0.596839427947998, 'pandas', 1), ('sfu-db/connector-x', 0.5911102890968323, 'data', 1), ('pyo3/pyo3', 0.5582752227783203, 'util', 1), ('tkrabel/bamboolib', 0.5383087396621704, 'pandas', 1), ('pyo3/maturin', 0.532139241695404, 'util', 1), ('rust... | 128 | 3 | null | 9.9 | 455 | 310 | 45 | 0 | 24 | 18 | 24 | 455 | 994 | 90 | 2.2 | 53 |
630 | util | https://github.com/pygments/pygments | [] | null | [] | [] | null | null | null | pygments/pygments | pygments | 1,487 | 579 | 33 | Python | http://pygments.org/ | Pygments is a generic syntax highlighter written in Python | pygments | 2024-01-13 | 2019-08-31 | 230 | 6.453193 | https://avatars.githubusercontent.com/u/50935516?v=4 | Pygments is a generic syntax highlighter written in Python | ['syntax-highlighting'] | ['syntax-highlighting'] | 2024-01-13 | [('hhatto/autopep8', 0.600104570388794, 'util', 0), ('grantjenks/blue', 0.5901092886924744, 'util', 0), ('pypy/pypy', 0.5847700834274292, 'util', 0), ('python/cpython', 0.5650127530097961, 'util', 0), ('willmcgugan/rich', 0.5573404431343079, 'term', 1), ('google/yapf', 0.5552298426628113, 'util', 0), ('instagram/libcst... | 821 | 5 | null | 7.12 | 137 | 107 | 53 | 0 | 7 | 15 | 7 | 137 | 282 | 90 | 2.1 | 53 |
1,558 | ml | https://github.com/huggingface/huggingface_hub | [] | null | [] | [] | null | null | null | huggingface/huggingface_hub | huggingface_hub | 1,449 | 354 | 58 | Python | https://huggingface.co/docs/huggingface_hub | The official Python client for the Huggingface Hub. | huggingface | 2024-01-14 | 2020-12-22 | 162 | 8.944444 | https://avatars.githubusercontent.com/u/25720743?v=4 | The official Python client for the Huggingface Hub. | ['deep-learning', 'machine-learning', 'model-hub', 'models', 'natural-language-processing', 'pretrained-models', 'pytorch'] | ['deep-learning', 'machine-learning', 'model-hub', 'models', 'natural-language-processing', 'pretrained-models', 'pytorch'] | 2024-01-12 | [('skorch-dev/skorch', 0.6804894804954529, 'ml-dl', 2), ('aws/sagemaker-python-sdk', 0.6623826026916504, 'ml', 2), ('huggingface/exporters', 0.6611513495445251, 'ml', 3), ('kubeflow/fairing', 0.624878466129303, 'ml-ops', 0), ('huggingface/transformers', 0.6154810190200806, 'nlp', 6), ('gradio-app/gradio', 0.61307507753... | 127 | 2 | null | 7.19 | 267 | 213 | 37 | 0 | 25 | 32 | 25 | 265 | 759 | 90 | 2.9 | 53 |
1,724 | llm | https://github.com/ray-project/ray-llm | [] | null | [] | [] | null | null | null | ray-project/ray-llm | ray-llm | 949 | 61 | 21 | Python | https://aviary.anyscale.com | RayLLM - LLMs on Ray | ray-project | 2024-01-13 | 2023-05-31 | 34 | 27.22541 | https://avatars.githubusercontent.com/u/22125274?v=4 | RayLLM - LLMs on Ray | ['distributed-systems', 'large-language-models', 'llm', 'llm-inference', 'llm-serving', 'llmops', 'ray', 'serving', 'transformers'] | ['distributed-systems', 'large-language-models', 'llm', 'llm-inference', 'llm-serving', 'llmops', 'ray', 'serving', 'transformers'] | 2024-01-08 | [('vllm-project/vllm', 0.7471011877059937, 'llm', 3), ('bentoml/openllm', 0.6621026396751404, 'ml-ops', 4), ('predibase/lorax', 0.6269615888595581, 'llm', 5), ('artidoro/qlora', 0.6143306493759155, 'llm', 0), ('salesforce/xgen', 0.6136285662651062, 'llm', 2), ('ray-project/ray-educational-materials', 0.6102384924888611... | 21 | 5 | null | 3.06 | 54 | 20 | 8 | 0 | 10 | 15 | 10 | 54 | 56 | 90 | 1 | 53 |
688 | ml-dl | https://github.com/iperov/deepfacelab | [] | null | [] | [] | null | null | null | iperov/deepfacelab | DeepFaceLab | 44,089 | 9,977 | 1,114 | Python | null | DeepFaceLab is the leading software for creating deepfakes. | iperov | 2024-01-14 | 2018-06-04 | 295 | 149.381897 | null | DeepFaceLab is the leading software for creating deepfakes. | ['arxiv', 'creating-deepfakes', 'deep-face-swap', 'deep-learning', 'deep-neural-networks', 'deepface', 'deepfacelab', 'deepfakes', 'deeplearning', 'face-swap', 'faceswap', 'fakeapp', 'machine-learning', 'neural-nets', 'neural-networks'] | ['arxiv', 'creating-deepfakes', 'deep-face-swap', 'deep-learning', 'deep-neural-networks', 'deepface', 'deepfacelab', 'deepfakes', 'deeplearning', 'face-swap', 'faceswap', 'fakeapp', 'machine-learning', 'neural-nets', 'neural-networks'] | 2023-04-27 | [('deepfakes/faceswap', 0.8627434968948364, 'ml-dl', 12), ('nvidia/deeplearningexamples', 0.5346398949623108, 'ml-dl', 1), ('open-mmlab/mmediting', 0.5308938026428223, 'ml', 1), ('huggingface/huggingface_hub', 0.5282143950462341, 'ml', 2), ('rwightman/pytorch-image-models', 0.5256627798080444, 'ml-dl', 0), ('fepegar/to... | 22 | 0 | null | 0.02 | 11 | 2 | 68 | 9 | 0 | 0 | 0 | 11 | 5 | 90 | 0.5 | 52 |
933 | llm | https://github.com/karpathy/mingpt | [] | null | [] | [] | null | null | null | karpathy/mingpt | minGPT | 17,452 | 2,101 | 249 | Python | null | A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training | karpathy | 2024-01-14 | 2020-08-17 | 180 | 96.878668 | null | A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training | [] | [] | 2023-01-08 | [('ist-daslab/gptq', 0.7072771787643433, 'llm', 0), ('minimaxir/gpt-2-simple', 0.6132301688194275, 'llm', 0), ('nvidia/apex', 0.6042015552520752, 'ml-dl', 0), ('bigscience-workshop/megatron-deepspeed', 0.6039530634880066, 'llm', 0), ('microsoft/megatron-deepspeed', 0.6039530634880066, 'llm', 0), ('nielsrogge/transforme... | 15 | 4 | null | 0 | 5 | 1 | 42 | 12 | 0 | 0 | 0 | 5 | 4 | 90 | 0.8 | 52 |
505 | ml | https://github.com/tensorflow/tensor2tensor | [] | null | [] | [] | null | null | null | tensorflow/tensor2tensor | tensor2tensor | 14,478 | 3,407 | 468 | Python | null | Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. | tensorflow | 2024-01-14 | 2017-06-15 | 345 | 41.878512 | https://avatars.githubusercontent.com/u/15658638?v=4 | Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. | ['deep-learning', 'machine-learning', 'machine-translation', 'reinforcement-learning', 'tpu'] | ['deep-learning', 'machine-learning', 'machine-translation', 'reinforcement-learning', 'tpu'] | 2023-04-01 | [('tensorlayer/tensorlayer', 0.6871770024299622, 'ml-rl', 2), ('huggingface/datasets', 0.6564465761184692, 'nlp', 2), ('tensorflow/tensorflow', 0.6497355103492737, 'ml-dl', 2), ('unity-technologies/ml-agents', 0.6379924416542053, 'ml-rl', 3), ('microsoft/deepspeed', 0.6303361058235168, 'ml-dl', 2), ('explosion/thinc', ... | 244 | 7 | null | 0.02 | 0 | 0 | 80 | 10 | 0 | 12 | 12 | 0 | 0 | 90 | 0 | 52 |
1,644 | util | https://github.com/dbader/schedule | ['scheduler'] | null | [] | [] | 1 | null | null | dbader/schedule | schedule | 11,297 | 996 | 216 | Python | https://schedule.readthedocs.io/ | Python job scheduling for humans. | dbader | 2024-01-13 | 2013-05-19 | 558 | 20.235159 | null | Python job scheduling for humans. | [] | ['scheduler'] | 2023-12-10 | [('agronholm/apscheduler', 0.7123571634292603, 'util', 0), ('dask/dask', 0.5425211191177368, 'perf', 0), ('pyinvoke/invoke', 0.514901876449585, 'util', 0)] | 59 | 5 | null | 0.27 | 16 | 6 | 130 | 1 | 0 | 2 | 2 | 16 | 29 | 90 | 1.8 | 52 |
166 | nlp | https://github.com/doccano/doccano | [] | null | [] | [] | null | null | null | doccano/doccano | doccano | 8,649 | 1,653 | 129 | Python | https://doccano.herokuapp.com | Open source annotation tool for machine learning practitioners. | doccano | 2024-01-14 | 2018-05-09 | 298 | 28.940249 | https://avatars.githubusercontent.com/u/58067660?v=4 | Open source annotation tool for machine learning practitioners. | ['annotation-tool', 'data-labeling', 'dataset', 'datasets', 'machine-learning', 'natural-language-processing', 'nuxt', 'nuxtjs', 'text-annotation', 'vue', 'vuejs'] | ['annotation-tool', 'data-labeling', 'dataset', 'datasets', 'machine-learning', 'natural-language-processing', 'nuxt', 'nuxtjs', 'text-annotation', 'vue', 'vuejs'] | 2023-08-10 | [('argilla-io/argilla', 0.6546259522438049, 'nlp', 4), ('mlflow/mlflow', 0.6210007667541504, 'ml-ops', 1), ('hegelai/prompttools', 0.6014738082885742, 'llm', 1), ('rasahq/rasa', 0.5829582214355469, 'llm', 2), ('tensorflow/tensorflow', 0.5740697383880615, 'ml-dl', 1), ('microsoft/nni', 0.573647141456604, 'ml', 1), ('tig... | 104 | 4 | null | 1.87 | 49 | 9 | 69 | 5 | 1 | 6 | 1 | 49 | 62 | 90 | 1.3 | 52 |
28 | ml-dl | https://github.com/google/trax | [] | null | [] | [] | null | null | null | google/trax | trax | 7,858 | 818 | 148 | Python | null | Trax — Deep Learning with Clear Code and Speed | google | 2024-01-14 | 2019-10-05 | 225 | 34.858048 | https://avatars.githubusercontent.com/u/1342004?v=4 | Trax — Deep Learning with Clear Code and Speed | ['deep-learning', 'deep-reinforcement-learning', 'jax', 'machine-learning', 'numpy', 'reinforcement-learning', 'transformer'] | ['deep-learning', 'deep-reinforcement-learning', 'jax', 'machine-learning', 'numpy', 'reinforcement-learning', 'transformer'] | 2023-11-15 | [('keras-team/keras', 0.7093995809555054, 'ml-dl', 3), ('keras-rl/keras-rl', 0.6790956258773804, 'ml-rl', 2), ('tensorlayer/tensorlayer', 0.6657304167747498, 'ml-rl', 2), ('explosion/thinc', 0.6631956696510315, 'ml-dl', 3), ('huggingface/transformers', 0.659750759601593, 'nlp', 4), ('deepmind/dm-haiku', 0.6491378545761... | 79 | 5 | null | 0.1 | 8 | 3 | 52 | 2 | 0 | 4 | 4 | 8 | 4 | 90 | 0.5 | 52 |
646 | profiling | https://github.com/joerick/pyinstrument | [] | null | [] | [] | null | null | null | joerick/pyinstrument | pyinstrument | 5,802 | 235 | 53 | Python | https://pyinstrument.readthedocs.io/ | 🚴 Call stack profiler for Python. Shows you why your code is slow! | joerick | 2024-01-13 | 2014-03-13 | 515 | 11.250416 | null | 🚴 Call stack profiler for Python. Shows you why your code is slow! | ['async', 'django', 'performance', 'profile', 'profiler'] | ['async', 'django', 'performance', 'profile', 'profiler'] | 2024-01-06 | [('sumerc/yappi', 0.6088473200798035, 'profiling', 2), ('benfred/py-spy', 0.5834751129150391, 'profiling', 1), ('jiffyclub/snakeviz', 0.5636839866638184, 'profiling', 0), ('pythonspeed/filprofiler', 0.5218971967697144, 'profiling', 0), ('pyutils/line_profiler', 0.5132960677146912, 'profiling', 0)] | 55 | 7 | null | 1.98 | 18 | 10 | 120 | 0 | 5 | 6 | 5 | 18 | 34 | 90 | 1.9 | 52 |
1,167 | study | https://github.com/gkamradt/langchain-tutorials | [] | null | [] | [] | null | null | null | gkamradt/langchain-tutorials | langchain-tutorials | 5,691 | 1,717 | 97 | Jupyter Notebook | null | Overview and tutorial of the LangChain Library | gkamradt | 2024-01-14 | 2023-02-13 | 50 | 113.495726 | null | Overview and tutorial of the LangChain Library | [] | [] | 2023-11-23 | [('prefecthq/langchain-prefect', 0.7797976732254028, 'llm', 0), ('langchain-ai/langgraph', 0.6401094794273376, 'llm', 0), ('logspace-ai/langflow', 0.5531355142593384, 'llm', 0), ('alphasecio/langchain-examples', 0.5529564023017883, 'llm', 0), ('langchain-ai/chat-langchain', 0.5390220284461975, 'llm', 0), ('langchain-ai... | 17 | 4 | null | 1.75 | 1 | 0 | 11 | 2 | 0 | 0 | 0 | 1 | 0 | 90 | 0 | 52 |
15 | ml-dl | https://github.com/skorch-dev/skorch | [] | null | [] | [] | null | null | null | skorch-dev/skorch | skorch | 5,518 | 379 | 82 | Jupyter Notebook | null | A scikit-learn compatible neural network library that wraps PyTorch | skorch-dev | 2024-01-13 | 2017-07-18 | 341 | 16.181818 | https://avatars.githubusercontent.com/u/47992320?v=4 | A scikit-learn compatible neural network library that wraps PyTorch | ['huggingface', 'machine-learning', 'pytorch', 'scikit-learn'] | ['huggingface', 'machine-learning', 'pytorch', 'scikit-learn'] | 2024-01-08 | [('pytorch/ignite', 0.8268391489982605, 'ml-dl', 2), ('rasbt/machine-learning-book', 0.777802050113678, 'study', 3), ('intel/intel-extension-for-pytorch', 0.7512941360473633, 'perf', 2), ('mrdbourke/pytorch-deep-learning', 0.6955669522285461, 'study', 2), ('nvidia/apex', 0.6882312893867493, 'ml-dl', 0), ('huggingface/h... | 61 | 5 | null | 0.96 | 18 | 13 | 79 | 0 | 3 | 3 | 3 | 18 | 29 | 90 | 1.6 | 52 |
823 | typing | https://github.com/python-attrs/attrs | [] | null | [] | [] | 1 | null | null | python-attrs/attrs | attrs | 4,977 | 388 | 65 | Python | https://www.attrs.org/ | Python Classes Without Boilerplate | python-attrs | 2024-01-13 | 2015-01-27 | 470 | 10.589362 | https://avatars.githubusercontent.com/u/25880274?v=4 | Python Classes Without Boilerplate | ['attributes', 'boilerplate', 'classes', 'oop'] | ['attributes', 'boilerplate', 'classes', 'oop'] | 2024-01-13 | [('martinheinz/python-project-blueprint', 0.521111011505127, 'template', 1), ('landscapeio/prospector', 0.5136226415634155, 'util', 0), ('xrudelis/pytrait', 0.5021693110466003, 'util', 0)] | 154 | 3 | null | 3.29 | 49 | 36 | 109 | 0 | 2 | 3 | 2 | 49 | 124 | 90 | 2.5 | 52 |
213 | data | https://github.com/facebookresearch/augly | [] | null | [] | [] | null | null | null | facebookresearch/augly | AugLy | 4,853 | 295 | 67 | Python | https://ai.facebook.com/blog/augly-a-new-data-augmentation-library-to-help-build-more-robust-ai-models/ | A data augmentations library for audio, image, text, and video. | facebookresearch | 2024-01-12 | 2021-06-09 | 137 | 35.203109 | https://avatars.githubusercontent.com/u/16943930?v=4 | A data augmentations library for audio, image, text, and video. | [] | [] | 2023-11-08 | [('albumentations-team/albumentations', 0.6632611751556396, 'ml-dl', 0), ('mdbloice/augmentor', 0.6478663086891174, 'ml', 0), ('aleju/imgaug', 0.5716978311538696, 'ml', 0), ('nomic-ai/nomic', 0.528243899345398, 'nlp', 0), ('researchmm/sttn', 0.5215305089950562, 'ml-dl', 0)] | 34 | 3 | null | 0.21 | 6 | 2 | 32 | 2 | 0 | 3 | 3 | 6 | 14 | 90 | 2.3 | 52 |
92 | ml | https://github.com/uber/causalml | [] | null | [] | [] | null | null | null | uber/causalml | causalml | 4,514 | 753 | 80 | Python | null | Uplift modeling and causal inference with machine learning algorithms | uber | 2024-01-13 | 2019-07-09 | 238 | 18.966387 | https://avatars.githubusercontent.com/u/538264?v=4 | Uplift modeling and causal inference with machine learning algorithms | ['causal-inference', 'incubation', 'machine-learning', 'uplift-modeling'] | ['causal-inference', 'incubation', 'machine-learning', 'uplift-modeling'] | 2024-01-12 | [('py-why/econml', 0.5542822480201721, 'ml', 2)] | 59 | 4 | null | 1.6 | 90 | 74 | 55 | 0 | 2 | 3 | 2 | 90 | 90 | 90 | 1 | 52 |
199 | viz | https://github.com/man-group/dtale | [] | null | [] | [] | null | null | null | man-group/dtale | dtale | 4,398 | 371 | 73 | TypeScript | http://alphatechadmin.pythonanywhere.com | Visualizer for pandas data structures | man-group | 2024-01-14 | 2019-07-15 | 237 | 18.545783 | https://avatars.githubusercontent.com/u/5859004?v=4 | Visualizer for pandas data structures | ['data-analysis', 'data-science', 'data-visualization', 'flask', 'ipython', 'jupyter-notebook', 'pandas', 'plotly-dash', 'python27', 'react', 'react-virtualized', 'visualization', 'xarray'] | ['data-analysis', 'data-science', 'data-visualization', 'flask', 'ipython', 'jupyter-notebook', 'pandas', 'plotly-dash', 'python27', 'react', 'react-virtualized', 'visualization', 'xarray'] | 2024-01-05 | [('mwaskom/seaborn', 0.73142409324646, 'viz', 3), ('holoviz/panel', 0.7240487337112427, 'viz', 0), ('kanaries/pygwalker', 0.7181293368339539, 'pandas', 3), ('lux-org/lux', 0.7073760032653809, 'viz', 3), ('holoviz/holoviz', 0.7002979516983032, 'viz', 0), ('bokeh/bokeh', 0.6867046356201172, 'viz', 1), ('plotly/plotly.py'... | 30 | 2 | null | 2.42 | 30 | 18 | 55 | 0 | 30 | 37 | 30 | 30 | 42 | 90 | 1.4 | 52 |
1,779 | viz | https://github.com/renpy/renpy | [] | null | [] | [] | null | null | null | renpy/renpy | renpy | 4,311 | 648 | 144 | Ren'Py | http://www.renpy.org/ | The Ren'Py Visual Novel Engine | renpy | 2024-01-14 | 2012-06-28 | 604 | 7.128987 | https://avatars.githubusercontent.com/u/1900740?v=4 | The Ren'Py Visual Novel Engine | ['engine', 'game', 'novel', 'renpy', 'visual', 'visual-novel'] | ['engine', 'game', 'novel', 'renpy', 'visual', 'visual-novel'] | 2024-01-14 | [('pokepetter/ursina', 0.6157830357551575, 'gamedev', 0), ('kitao/pyxel', 0.5945414304733276, 'gamedev', 1), ('pygame/pygame', 0.5524816513061523, 'gamedev', 0), ('panda3d/panda3d', 0.5438269972801208, 'gamedev', 0), ('pyscript/pyscript-cli', 0.5380860567092896, 'web', 0), ('fastai/fastcore', 0.5279468894004822, 'util'... | 194 | 1 | null | 31.38 | 346 | 293 | 141 | 0 | 8 | 47 | 8 | 345 | 606 | 90 | 1.8 | 52 |
356 | data | https://github.com/amundsen-io/amundsen | [] | null | [] | [] | null | null | null | amundsen-io/amundsen | amundsen | 4,179 | 947 | 237 | Python | https://www.amundsen.io/amundsen/ | Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data. | amundsen-io | 2024-01-13 | 2019-05-14 | 246 | 16.987805 | https://avatars.githubusercontent.com/u/67136999?v=4 | Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data. | ['amundsen', 'data-catalog', 'data-discovery', 'linuxfoundation', 'metadata'] | ['amundsen', 'data-catalog', 'data-discovery', 'linuxfoundation', 'metadata'] | 2024-01-11 | [] | 222 | 2 | null | 1.42 | 36 | 21 | 57 | 0 | 7 | 28 | 7 | 36 | 42 | 90 | 1.2 | 52 |
755 | sim | https://github.com/quantumlib/cirq | [] | null | [] | [] | null | null | null | quantumlib/cirq | Cirq | 4,027 | 948 | 192 | Python | null | A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits. | quantumlib | 2024-01-14 | 2017-12-14 | 319 | 12.595621 | https://avatars.githubusercontent.com/u/31279789?v=4 | A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits. | ['cirq', 'nisq', 'quantum-algorithms', 'quantum-circuits', 'quantum-computing'] | ['cirq', 'nisq', 'quantum-algorithms', 'quantum-circuits', 'quantum-computing'] | 2024-01-13 | [('cqcl/lambeq', 0.6558890342712402, 'nlp', 0), ('pyscf/pyscf', 0.6541039347648621, 'sim', 0), ('cqcl/tket', 0.6193458437919617, 'util', 1), ('jackhidary/quantumcomputingbook', 0.5691633224487305, 'study', 2), ('qiskit/qiskit', 0.5546154975891113, 'sim', 1), ('netket/netket', 0.5286350250244141, 'sim', 0), ('zeromq/pyz... | 213 | 2 | null | 4.87 | 166 | 98 | 74 | 0 | 2 | 4 | 2 | 166 | 243 | 90 | 1.5 | 52 |
802 | web | https://github.com/fastapi-users/fastapi-users | [] | null | [] | [] | null | null | null | fastapi-users/fastapi-users | fastapi-users | 3,772 | 341 | 38 | Python | https://fastapi-users.github.io/fastapi-users/ | Ready-to-use and customizable users management for FastAPI | fastapi-users | 2024-01-14 | 2019-10-05 | 225 | 16.732573 | https://avatars.githubusercontent.com/u/89578248?v=4 | Ready-to-use and customizable users management for FastAPI | ['async', 'asyncio', 'fastapi', 'fastapi-users', 'starlette', 'users'] | ['async', 'asyncio', 'fastapi', 'fastapi-users', 'starlette', 'users'] | 2023-12-28 | [('dmontagu/fastapi_client', 0.6202594637870789, 'web', 0), ('zhanymkanov/fastapi-best-practices', 0.6014936566352844, 'study', 1), ('tiangolo/fastapi', 0.599251925945282, 'web', 4), ('s3rius/fastapi-template', 0.595072329044342, 'web', 2), ('fastapi-admin/fastapi-admin', 0.5555592775344849, 'web', 1), ('asacristani/fa... | 62 | 4 | null | 1.1 | 20 | 15 | 52 | 1 | 9 | 23 | 9 | 20 | 35 | 90 | 1.8 | 52 |
171 | ml | https://github.com/ourownstory/neural_prophet | [] | null | [] | [] | null | null | null | ourownstory/neural_prophet | neural_prophet | 3,494 | 453 | 53 | Python | https://neuralprophet.com | NeuralProphet: A simple forecasting package | ourownstory | 2024-01-12 | 2020-05-04 | 195 | 17.904832 | null | NeuralProphet: A simple forecasting package | ['artificial-intelligence', 'autoregression', 'deep-learning', 'fbprophet', 'forecast', 'forecasting', 'forecasting-algorithm', 'forecasting-model', 'machine-learning', 'neural', 'neural-network', 'neuralprophet', 'prediction', 'prophet', 'pytorch', 'seasonality', 'time-series', 'timeseries', 'trend'] | ['artificial-intelligence', 'autoregression', 'deep-learning', 'fbprophet', 'forecast', 'forecasting', 'forecasting-algorithm', 'forecasting-model', 'machine-learning', 'neural', 'neural-network', 'neuralprophet', 'prediction', 'prophet', 'pytorch', 'seasonality', 'time-series', 'timeseries', 'trend'] | 2023-12-23 | [('winedarksea/autots', 0.6846452355384827, 'time-series', 4), ('nixtla/statsforecast', 0.6677179336547852, 'time-series', 6), ('awslabs/autogluon', 0.6234149932861328, 'ml', 5), ('salesforce/deeptime', 0.5901058316230774, 'time-series', 3), ('aistream-peelout/flow-forecast', 0.5880416035652161, 'time-series', 4), ('mi... | 50 | 2 | null | 3.35 | 65 | 48 | 45 | 1 | 11 | 8 | 11 | 65 | 107 | 90 | 1.6 | 52 |
1,635 | util | https://github.com/osohq/oso | ['authorization'] | null | [] | [] | null | null | null | osohq/oso | oso | 3,335 | 169 | 31 | Rust | https://docs.osohq.com | Oso is a batteries-included framework for building authorization in your application. | osohq | 2024-01-14 | 2020-05-04 | 195 | 17.090044 | https://avatars.githubusercontent.com/u/47367300?v=4 | Oso is a batteries-included framework for building authorization in your application. | ['abac', 'access-control', 'authorization', 'authorization-framework', 'go', 'java', 'logic-programming', 'nodejs', 'policy-engine', 'rbac', 'rbac-authorization', 'rbac-roles', 'ruby', 'rust', 'security'] | ['abac', 'access-control', 'authorization', 'authorization-framework', 'go', 'java', 'logic-programming', 'nodejs', 'policy-engine', 'rbac', 'rbac-authorization', 'rbac-roles', 'ruby', 'rust', 'security'] | 2024-01-13 | [] | 66 | 5 | null | 0.81 | 17 | 8 | 45 | 0 | 7 | 54 | 7 | 17 | 27 | 90 | 1.6 | 52 |
267 | jupyter | https://github.com/jupyterlab/jupyterlab-desktop | [] | null | [] | [] | null | null | null | jupyterlab/jupyterlab-desktop | jupyterlab-desktop | 3,199 | 297 | 52 | TypeScript | null | JupyterLab desktop application, based on Electron. | jupyterlab | 2024-01-12 | 2017-05-04 | 351 | 9.095451 | https://avatars.githubusercontent.com/u/22800682?v=4 | JupyterLab desktop application, based on Electron. | ['jupyter', 'jupyter-notebook', 'jupyterlab'] | ['jupyter', 'jupyter-notebook', 'jupyterlab'] | 2024-01-05 | [('jupyterlab/jupyterlab', 0.7525447607040405, 'jupyter', 2), ('voila-dashboards/voila', 0.7262636423110962, 'jupyter', 2), ('jupyter/notebook', 0.7161470651626587, 'jupyter', 2), ('jupyter-widgets/ipywidgets', 0.7082852721214294, 'jupyter', 0), ('jupyter/nbformat', 0.6620615720748901, 'jupyter', 0), ('mwouts/jupytext'... | 39 | 5 | null | 4.31 | 52 | 37 | 82 | 0 | 11 | 5 | 11 | 52 | 113 | 90 | 2.2 | 52 |
807 | data | https://github.com/deepchecks/deepchecks | [] | null | [] | [] | null | null | null | deepchecks/deepchecks | deepchecks | 3,169 | 229 | 16 | Python | https://docs.deepchecks.com/stable | Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production. | deepchecks | 2024-01-13 | 2021-10-11 | 120 | 26.376932 | https://avatars.githubusercontent.com/u/92298186?v=4 | Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production. | ['data-drift', 'data-science', 'data-validation', 'deep-learning', 'html-report', 'jupyter-notebook', 'machine-learning', 'ml', 'mlops', 'model-monitoring', 'model-validation', 'pandas-dataframe', 'pytorch'] | ['data-drift', 'data-science', 'data-validation', 'deep-learning', 'html-report', 'jupyter-notebook', 'machine-learning', 'ml', 'mlops', 'model-monitoring', 'model-validation', 'pandas-dataframe', 'pytorch'] | 2023-12-18 | [('evidentlyai/evidently', 0.6157994866371155, 'ml-ops', 8), ('polyaxon/polyaxon', 0.5667403340339661, 'ml-ops', 6), ('microsoft/deepspeed', 0.5651904940605164, 'ml-dl', 3), ('determined-ai/determined', 0.5619574189186096, 'ml-ops', 5), ('huggingface/datasets', 0.5608824491500854, 'nlp', 3), ('wandb/client', 0.55738073... | 52 | 2 | null | 4.63 | 51 | 43 | 28 | 1 | 13 | 27 | 13 | 51 | 31 | 90 | 0.6 | 52 |
1,595 | ml-ops | https://github.com/towhee-io/towhee | [] | null | [] | [] | null | null | null | towhee-io/towhee | towhee | 2,902 | 243 | 42 | Python | https://towhee.io | Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast. | towhee-io | 2024-01-13 | 2021-07-13 | 133 | 21.819549 | https://avatars.githubusercontent.com/u/87362374?v=4 | Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast. | ['computer-vision', 'convolutional-networks', 'embedding-vectors', 'embeddings', 'feature-extraction', 'feature-vector', 'image-processing', 'image-retrieval', 'llm', 'machine-learning', 'milvus', 'pipeline', 'towhee', 'transformer', 'unstructured-data', 'video-processing', 'vision-transformer', 'vit'] | ['computer-vision', 'convolutional-networks', 'embedding-vectors', 'embeddings', 'feature-extraction', 'feature-vector', 'image-processing', 'image-retrieval', 'llm', 'machine-learning', 'milvus', 'pipeline', 'towhee', 'transformer', 'unstructured-data', 'video-processing', 'vision-transformer', 'vit'] | 2023-12-04 | [('huggingface/datasets', 0.5772765278816223, 'nlp', 2), ('awslabs/autogluon', 0.5480068325996399, 'ml', 2), ('roboflow/supervision', 0.544347882270813, 'ml', 4), ('lutzroeder/netron', 0.5428910851478577, 'ml', 1), ('activeloopai/deeplake', 0.5378854870796204, 'ml-ops', 4), ('deci-ai/super-gradients', 0.534018158912658... | 34 | 1 | null | 3.27 | 26 | 24 | 30 | 1 | 5 | 8 | 5 | 26 | 90 | 90 | 3.5 | 52 |
1,509 | llm | https://github.com/defog-ai/sqlcoder | ['language-model', 'sql'] | null | [] | [] | 1 | null | null | defog-ai/sqlcoder | sqlcoder | 1,962 | 114 | 22 | Jupyter Notebook | null | SoTA LLM for converting natural language questions to SQL queries | defog-ai | 2024-01-13 | 2023-08-17 | 23 | 82.73494 | https://avatars.githubusercontent.com/u/79135711?v=4 | SoTA LLM for converting natural language questions to SQL queries | [] | ['language-model', 'sql'] | 2023-11-15 | [('night-chen/toolqa', 0.5368439555168152, 'llm', 0), ('srush/minichain', 0.512403130531311, 'llm', 0), ('neulab/prompt2model', 0.5062905550003052, 'llm', 1)] | 5 | 3 | null | 0.92 | 29 | 9 | 5 | 2 | 0 | 0 | 0 | 29 | 45 | 90 | 1.6 | 52 |
466 | ml | https://github.com/huggingface/optimum | [] | null | [] | [] | null | null | null | huggingface/optimum | optimum | 1,879 | 316 | 53 | Python | https://huggingface.co/docs/optimum/main/ | 🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools | huggingface | 2024-01-13 | 2021-07-20 | 132 | 14.234848 | https://avatars.githubusercontent.com/u/25720743?v=4 | 🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools | ['graphcore', 'habana', 'inference', 'intel', 'onnx', 'onnxruntime', 'optimization', 'pytorch', 'quantization', 'tflite', 'training', 'transformers'] | ['graphcore', 'habana', 'inference', 'intel', 'onnx', 'onnxruntime', 'optimization', 'pytorch', 'quantization', 'tflite', 'training', 'transformers'] | 2024-01-12 | [('huggingface/transformers', 0.682058572769165, 'nlp', 1), ('huggingface/peft', 0.6415036916732788, 'llm', 2), ('ist-daslab/gptq', 0.6178866624832153, 'llm', 0), ('karpathy/mingpt', 0.5994217395782471, 'llm', 0), ('alignmentresearch/tuned-lens', 0.5732378363609314, 'ml-interpretability', 2), ('intel/intel-extension-fo... | 89 | 1 | null | 9.33 | 249 | 165 | 30 | 0 | 30 | 21 | 30 | 249 | 333 | 90 | 1.3 | 52 |
1,891 | llm | https://github.com/cg123/mergekit | [] | null | [] | [] | null | null | null | cg123/mergekit | mergekit | 1,458 | 128 | 23 | Python | null | Tools for merging pretrained large language models. | cg123 | 2024-01-14 | 2023-08-21 | 23 | 63 | null | Tools for merging pretrained large language models. | ['llama', 'llm', 'model-merging'] | ['llama', 'llm', 'model-merging'] | 2024-01-14 | [('infinitylogesh/mutate', 0.6713061332702637, 'nlp', 0), ('juncongmoo/pyllama', 0.6644551753997803, 'llm', 0), ('ai21labs/lm-evaluation', 0.6523741483688354, 'llm', 0), ('hannibal046/awesome-llm', 0.6510716080665588, 'study', 0), ('ctlllll/llm-toolmaker', 0.6498943567276001, 'llm', 0), ('young-geng/easylm', 0.64665031... | 4 | 0 | null | 2.29 | 107 | 65 | 5 | 0 | 1 | 5 | 1 | 107 | 262 | 90 | 2.4 | 52 |
1,170 | llm | https://github.com/chatarena/chatarena | [] | null | [] | [] | null | null | null | chatarena/chatarena | chatarena | 1,127 | 113 | 19 | Python | https://www.chatarena.org/ | ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs. | chatarena | 2024-01-12 | 2023-03-06 | 47 | 23.906061 | https://avatars.githubusercontent.com/u/62961550?v=4 | ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs. | ['ai', 'artificial-intelligence', 'chatgpt', 'gpt-4', 'large-language-models', 'multi-agent', 'multi-agent-reinforcement-learning', 'multi-agent-simulation', 'natural-language-processing'] | ['ai', 'artificial-intelligence', 'chatgpt', 'gpt-4', 'large-language-models', 'multi-agent', 'multi-agent-reinforcement-learning', 'multi-agent-simulation', 'natural-language-processing'] | 2023-12-21 | [('embedchain/embedchain', 0.6508777141571045, 'llm', 2), ('prefecthq/marvin', 0.6427308917045593, 'nlp', 1), ('rcgai/simplyretrieve', 0.6356537342071533, 'llm', 3), ('nomic-ai/gpt4all', 0.6325280070304871, 'llm', 0), ('microsoft/autogen', 0.6130094528198242, 'llm', 2), ('lm-sys/fastchat', 0.6125940680503845, 'llm', 0)... | 15 | 6 | null | 5.96 | 68 | 67 | 10 | 1 | 15 | 18 | 15 | 68 | 28 | 90 | 0.4 | 52 |
602 | util | https://github.com/norvig/pytudes | [] | null | [] | [] | null | null | null | norvig/pytudes | pytudes | 22,095 | 2,385 | 768 | Jupyter Notebook | null | Python programs, usually short, of considerable difficulty, to perfect particular skills. | norvig | 2024-01-13 | 2017-03-01 | 360 | 61.229216 | null | Python programs, usually short, of considerable difficulty, to perfect particular skills. | ['demonstrate-skills', 'practice', 'programming'] | ['demonstrate-skills', 'practice', 'programming'] | 2024-01-02 | [('python/cpython', 0.6239404082298279, 'util', 0), ('google/pyglove', 0.5999535322189331, 'util', 0), ('adafruit/circuitpython', 0.5722380876541138, 'util', 0), ('sympy/sympy', 0.5708892941474915, 'math', 0), ('amaargiru/pyroad', 0.5647484064102173, 'study', 0), ('pypy/pypy', 0.5617297887802124, 'util', 0), ('eleuther... | 44 | 3 | null | 0.65 | 0 | 0 | 84 | 0 | 0 | 0 | 0 | 0 | 0 | 90 | 0 | 51 |
370 | viz | https://github.com/marceloprates/prettymaps | [] | null | [] | [] | null | null | null | marceloprates/prettymaps | prettymaps | 10,652 | 541 | 83 | Jupyter Notebook | null | A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely libraries. | marceloprates | 2024-01-13 | 2021-03-05 | 151 | 70.277097 | null | A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely libraries. | ['cartography', 'generative-art', 'jupyter-notebook', 'maps', 'matplotlib', 'openstreetmap'] | ['cartography', 'generative-art', 'jupyter-notebook', 'maps', 'matplotlib', 'openstreetmap'] | 2023-02-15 | [('gboeing/osmnx', 0.6797459125518799, 'gis', 1), ('raphaelquast/eomaps', 0.6013832688331604, 'gis', 1), ('scitools/cartopy', 0.5919488072395325, 'gis', 2), ('holoviz/geoviews', 0.5674756765365601, 'gis', 0), ('gboeing/osmnx-examples', 0.562412440776825, 'gis', 2), ('gregorhd/mapcompare', 0.557414710521698, 'gis', 0), ... | 15 | 4 | null | 0.31 | 5 | 0 | 35 | 11 | 1 | 6 | 1 | 5 | 4 | 90 | 0.8 | 51 |
22 | nlp | https://github.com/facebookresearch/parlai | [] | null | [] | [] | null | null | null | facebookresearch/parlai | ParlAI | 10,381 | 2,091 | 287 | Python | https://parl.ai | A framework for training and evaluating AI models on a variety of openly available dialogue datasets. | facebookresearch | 2024-01-13 | 2017-04-24 | 353 | 29.396036 | https://avatars.githubusercontent.com/u/16943930?v=4 | A framework for training and evaluating AI models on a variety of openly available dialogue datasets. | [] | [] | 2023-11-03 | [('nvidia/nemo', 0.6826277375221252, 'nlp', 0), ('krohling/bondai', 0.680033266544342, 'llm', 0), ('deeppavlov/deeppavlov', 0.6255822777748108, 'nlp', 0), ('rasahq/rasa', 0.5971487164497375, 'llm', 0), ('lm-sys/fastchat', 0.5788213610649109, 'llm', 0), ('minimaxir/aitextgen', 0.5751350522041321, 'llm', 0), ('databricks... | 217 | 3 | null | 1.25 | 5 | 2 | 82 | 2 | 1 | 6 | 1 | 5 | 5 | 90 | 1 | 51 |
1,084 | util | https://github.com/pytube/pytube | [] | null | [] | [] | null | null | null | pytube/pytube | pytube | 9,837 | 2,177 | 194 | Python | https://pytube.io | A lightweight, dependency-free Python library (and command-line utility) for downloading YouTube Videos. | pytube | 2024-01-14 | 2012-03-18 | 619 | 15.884429 | https://avatars.githubusercontent.com/u/16789089?v=4 | A lightweight, dependency-free Python library (and command-line utility) for downloading YouTube Videos. | ['api-wrapper', 'pythonic', 'youtube'] | ['api-wrapper', 'pythonic', 'youtube'] | 2023-05-20 | [('yt-dlp/yt-dlp', 0.5481389164924622, 'util', 0), ('psycoguana/subredditmediadownloader', 0.5245307087898254, 'data', 0)] | 112 | 5 | null | 0.38 | 88 | 16 | 144 | 8 | 0 | 10 | 10 | 88 | 140 | 90 | 1.6 | 51 |
158 | util | https://github.com/pallets/jinja | [] | null | [] | [] | null | null | null | pallets/jinja | jinja | 9,717 | 1,591 | 251 | Python | https://jinja.palletsprojects.com | A very fast and expressive template engine. | pallets | 2024-01-13 | 2010-10-17 | 693 | 14.015866 | https://avatars.githubusercontent.com/u/16748505?v=4 | A very fast and expressive template engine. | ['jinja', 'jinja2', 'pallets', 'template-engine', 'templates'] | ['jinja', 'jinja2', 'pallets', 'template-engine', 'templates'] | 2024-01-10 | [('s3rius/fastapi-template', 0.5498924255371094, 'web', 0), ('sqlalchemy/mako', 0.54783034324646, 'template', 0), ('thereforegames/unprompted', 0.5376675128936768, 'diffusion', 1), ('django/django', 0.5016000270843506, 'web', 1), ('pallets/flask', 0.5012500882148743, 'web', 2)] | 306 | 4 | null | 0.96 | 37 | 21 | 161 | 0 | 1 | 4 | 1 | 37 | 45 | 90 | 1.2 | 51 |
142 | ml | https://github.com/featurelabs/featuretools | [] | null | [] | [] | 1 | null | null | featurelabs/featuretools | featuretools | 6,933 | 856 | 158 | Python | https://www.featuretools.com | An open source python library for automated feature engineering | featurelabs | 2024-01-13 | 2017-09-08 | 333 | 20.784154 | https://avatars.githubusercontent.com/u/12972388?v=4 | An open source python library for automated feature engineering | ['automated-feature-engineering', 'automated-machine-learning', 'automl', 'data-science', 'feature-engineering', 'machine-learning', 'scikit-learn'] | ['automated-feature-engineering', 'automated-machine-learning', 'automl', 'data-science', 'feature-engineering', 'machine-learning', 'scikit-learn'] | 2023-12-07 | [('google/temporian', 0.7070109844207764, 'time-series', 1), ('rasbt/mlxtend', 0.6914775371551514, 'ml', 2), ('pycaret/pycaret', 0.6861603856086731, 'ml', 2), ('microsoft/nni', 0.6769810914993286, 'ml', 5), ('automl/auto-sklearn', 0.6524330377578735, 'ml', 3), ('epistasislab/tpot', 0.6507097482681274, 'ml', 6), ('mljar... | 71 | 2 | null | 1.65 | 30 | 21 | 77 | 1 | 8 | 24 | 8 | 30 | 18 | 90 | 0.6 | 51 |
771 | study | https://github.com/nielsrogge/transformers-tutorials | [] | null | [] | [] | null | null | null | nielsrogge/transformers-tutorials | Transformers-Tutorials | 6,629 | 1,045 | 111 | Jupyter Notebook | null | This repository contains demos I made with the Transformers library by HuggingFace. | nielsrogge | 2024-01-13 | 2020-08-31 | 178 | 37.211708 | null | This repository contains demos I made with the Transformers library by HuggingFace. | ['bert', 'gpt-2', 'layoutlm', 'pytorch', 'transformers', 'vision-transformer'] | ['bert', 'gpt-2', 'layoutlm', 'pytorch', 'transformers', 'vision-transformer'] | 2024-01-11 | [('karpathy/mingpt', 0.6038249135017395, 'llm', 0), ('nvlabs/gcvit', 0.5923160910606384, 'diffusion', 1), ('huggingface/transformers', 0.5857082605361938, 'nlp', 2), ('bigscience-workshop/megatron-deepspeed', 0.5679675936698914, 'llm', 0), ('microsoft/megatron-deepspeed', 0.5679675936698914, 'llm', 0), ('huggingface/ex... | 5 | 2 | null | 1.48 | 42 | 7 | 41 | 0 | 0 | 0 | 0 | 42 | 73 | 90 | 1.7 | 51 |
1,063 | diffusion | https://github.com/timothybrooks/instruct-pix2pix | [] | PyTorch implementation of InstructPix2Pix, an instruction-based image editing model, based on the original CompVis/stable_diffusion repo. | [] | [] | null | null | null | timothybrooks/instruct-pix2pix | instruct-pix2pix | 5,565 | 495 | 64 | Python | null | null | timothybrooks | 2024-01-13 | 2023-01-09 | 55 | 100.919689 | null | PyTorch implementation of InstructPix2Pix, an instruction-based image editing model, based on the original CompVis/stable_diffusion repo. | [] | [] | 2023-01-31 | [('carson-katri/dream-textures', 0.5679231286048889, 'diffusion', 0), ('huggingface/diffusers', 0.5238240957260132, 'diffusion', 0), ('sanster/lama-cleaner', 0.5218861699104309, 'ml-dl', 0), ('compvis/latent-diffusion', 0.5207135081291199, 'diffusion', 0), ('stability-ai/stablediffusion', 0.5207132697105408, 'diffusion... | 13 | 3 | null | 0.1 | 10 | 3 | 12 | 12 | 0 | 0 | 0 | 10 | 10 | 90 | 1 | 51 |
1,907 | util | https://github.com/pypa/virtualenv | ['pip', 'venv', 'virtualenv'] | A tool to create isolated Python environments. Since Python 3.3, a subset of it has been integrated into the standard lib venv module. | [] | [] | null | null | null | pypa/virtualenv | virtualenv | 4,621 | 1,091 | 169 | Python | https://virtualenv.pypa.io | Virtual Python Environment builder | pypa | 2024-01-20 | 2011-03-06 | 673 | 6.863357 | https://avatars.githubusercontent.com/u/647025?v=4 | Virtual Python Environment builder | ['cython', 'jython', 'pypa', 'pypy', 'pypy3', 'virtualenv'] | ['cython', 'jython', 'pip', 'pypa', 'pypy', 'pypy3', 'venv', 'virtualenv'] | 2024-01-16 | [('pypa/pipenv', 0.6951494216918945, 'util', 3), ('pypa/hatch', 0.6300379633903503, 'util', 1), ('pyenv/pyenv', 0.6280038952827454, 'util', 2), ('pypa/pipx', 0.6216922998428345, 'util', 2), ('pypy/pypy', 0.6060330271720886, 'util', 0), ('pantsbuild/pex', 0.5755523443222046, 'util', 1), ('ofek/pyapp', 0.5487356781959534... | 113 | 5 | null | 2.17 | 35 | 26 | 157 | 0 | 17 | 17 | 17 | 35 | 74 | 90 | 2.1 | 51 |
286 | gis | https://github.com/geopandas/geopandas | ['geopandas', 'pandas', 'gis'] | null | [] | [] | 1 | null | null | geopandas/geopandas | geopandas | 4,017 | 908 | 106 | Python | http://geopandas.org/ | Python tools for geographic data | geopandas | 2024-01-13 | 2013-06-27 | 552 | 7.267769 | https://avatars.githubusercontent.com/u/8130715?v=4 | Python tools for geographic data | ['geoparquet', 'geospatial', 'pandas', 'spatial'] | ['geopandas', 'geoparquet', 'geospatial', 'gis', 'pandas', 'spatial'] | 2024-01-07 | [('artelys/geonetworkx', 0.7633013725280762, 'gis', 0), ('residentmario/geoplot', 0.7451832890510559, 'gis', 1), ('holoviz/spatialpandas', 0.6860671043395996, 'pandas', 2), ('opengeos/leafmap', 0.671466052532196, 'gis', 3), ('openeventdata/mordecai', 0.6333655714988708, 'gis', 0), ('raphaelquast/eomaps', 0.608457028865... | 216 | 4 | null | 3.25 | 141 | 85 | 128 | 0 | 6 | 3 | 6 | 141 | 211 | 90 | 1.5 | 51 |
157 | profiling | https://github.com/gaogaotiantian/viztracer | [] | null | [] | [] | null | null | null | gaogaotiantian/viztracer | viztracer | 3,909 | 343 | 48 | Python | https://viztracer.readthedocs.io/ | VizTracer is a low-overhead logging/debugging/profiling tool that can trace and visualize your python code execution. | gaogaotiantian | 2024-01-14 | 2020-08-05 | 181 | 21.494894 | null | VizTracer is a low-overhead logging/debugging/profiling tool that can trace and visualize your python code execution. | ['debugging', 'flamegraph', 'logging', 'profiling', 'tracer', 'visualization'] | ['debugging', 'flamegraph', 'logging', 'profiling', 'tracer', 'visualization'] | 2024-01-08 | [('alexmojaki/heartrate', 0.6707364320755005, 'debug', 1), ('alexmojaki/snoop', 0.623710036277771, 'debug', 2), ('pympler/pympler', 0.6162266731262207, 'perf', 0), ('ionelmc/python-hunter', 0.6034563779830933, 'debug', 2), ('landscapeio/prospector', 0.6018545627593994, 'util', 0), ('pyutils/line_profiler', 0.5905494689... | 25 | 3 | null | 0.79 | 25 | 14 | 42 | 0 | 2 | 23 | 2 | 25 | 52 | 90 | 2.1 | 51 |
183 | testing | https://github.com/tox-dev/tox | [] | null | [] | [] | null | null | null | tox-dev/tox | tox | 3,426 | 502 | 42 | Python | https://tox.wiki | Command line driven CI frontend and development task automation tool. | tox-dev | 2024-01-14 | 2016-09-17 | 384 | 8.911929 | https://avatars.githubusercontent.com/u/20345659?v=4 | Command line driven CI frontend and development task automation tool. | ['actions', 'appveyor', 'automation', 'azure-pipelines', 'circleci', 'cli', 'continuous-integration', 'gitlab', 'pep-621', 'testing', 'travis', 'venv', 'virtualenv'] | ['actions', 'appveyor', 'automation', 'azure-pipelines', 'circleci', 'cli', 'continuous-integration', 'gitlab', 'pep-621', 'testing', 'travis', 'venv', 'virtualenv'] | 2024-01-12 | [('ianmiell/shutit', 0.5560944080352783, 'util', 0), ('allegroai/clearml', 0.5439307689666748, 'ml-ops', 0), ('pydoit/doit', 0.5430145859718323, 'util', 0), ('zenml-io/zenml', 0.5314726233482361, 'ml-ops', 0), ('buildbot/buildbot', 0.5279530882835388, 'util', 1), ('pytest-dev/pytest-testinfra', 0.5243973731994629, 'tes... | 68 | 6 | null | 3 | 48 | 35 | 89 | 0 | 38 | 29 | 38 | 48 | 66 | 90 | 1.4 | 51 |
897 | util | https://github.com/pypi/warehouse | [] | null | [] | [] | null | null | null | pypi/warehouse | warehouse | 3,422 | 1,041 | 112 | Python | https://pypi.org | The Python Package Index | pypi | 2024-01-14 | 2013-03-30 | 565 | 6.052046 | https://avatars.githubusercontent.com/u/2964877?v=4 | The Python Package Index | ['package-registry', 'package-repository', 'pypi-source'] | ['package-registry', 'package-repository', 'pypi-source'] | 2024-01-12 | [('pdm-project/pdm', 0.6904469728469849, 'util', 0), ('indygreg/pyoxidizer', 0.6707281470298767, 'util', 0), ('mitsuhiko/rye', 0.6509472131729126, 'util', 0), ('pyodide/micropip', 0.6480095386505127, 'util', 0), ('pypa/flit', 0.6236358284950256, 'util', 0), ('pypa/hatch', 0.6159988641738892, 'util', 0), ('pypa/gh-actio... | 370 | 7 | null | 13.9 | 524 | 430 | 131 | 0 | 0 | 0 | 0 | 523 | 587 | 90 | 1.1 | 51 |
804 | ml-ops | https://github.com/ploomber/ploomber | [] | null | [] | [] | null | null | null | ploomber/ploomber | ploomber | 3,306 | 222 | 29 | Python | https://ploomber.io | The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️ | ploomber | 2024-01-14 | 2020-01-20 | 210 | 15.732155 | https://avatars.githubusercontent.com/u/60114551?v=4 | The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️ | ['data-engineering', 'data-science', 'jupyter', 'jupyter-notebooks', 'machine-learning', 'mlops', 'notebooks', 'papermill', 'pipelines', 'pycharm', 'vscode', 'workflow'] | ['data-engineering', 'data-science', 'jupyter', 'jupyter-notebooks', 'machine-learning', 'mlops', 'notebooks', 'papermill', 'pipelines', 'pycharm', 'vscode', 'workflow'] | 2024-01-03 | [('orchest/orchest', 0.862511932849884, 'ml-ops', 5), ('linealabs/lineapy', 0.739909827709198, 'jupyter', 0), ('mage-ai/mage-ai', 0.7089954614639282, 'ml-ops', 4), ('avaiga/taipy', 0.6359885334968567, 'data', 4), ('meltano/meltano', 0.6284797787666321, 'ml-ops', 2), ('kestra-io/kestra', 0.6272913217544556, 'ml-ops', 2)... | 80 | 1 | null | 1.37 | 24 | 16 | 48 | 0 | 0 | 29 | 29 | 24 | 68 | 90 | 2.8 | 51 |
1,383 | diffusion | https://github.com/mlc-ai/web-stable-diffusion | [] | null | [] | [] | null | null | null | mlc-ai/web-stable-diffusion | web-stable-diffusion | 3,273 | 196 | 33 | Jupyter Notebook | https://mlc.ai/web-stable-diffusion | Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support. | mlc-ai | 2024-01-13 | 2023-03-06 | 47 | 69.427273 | https://avatars.githubusercontent.com/u/106173866?v=4 | Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support. | ['deep-learning', 'stable-diffusion', 'tvm', 'web-assembly', 'webgpu', 'webml'] | ['deep-learning', 'stable-diffusion', 'tvm', 'web-assembly', 'webgpu', 'webml'] | 2023-07-18 | [('automatic1111/stable-diffusion-webui', 0.7200703024864197, 'diffusion', 2), ('thereforegames/unprompted', 0.6838393807411194, 'diffusion', 2), ('mlc-ai/web-llm', 0.6759905219078064, 'llm', 4), ('civitai/sd_civitai_extension', 0.6748091578483582, 'llm', 0), ('bentoml/onediffusion', 0.6144503355026245, 'diffusion', 1)... | 8 | 5 | null | 0.75 | 8 | 1 | 10 | 6 | 0 | 0 | 0 | 8 | 11 | 90 | 1.4 | 51 |
140 | viz | https://github.com/vispy/vispy | [] | null | [] | [] | null | null | null | vispy/vispy | vispy | 3,170 | 614 | 117 | Python | http://vispy.org | Main repository for Vispy | vispy | 2024-01-12 | 2013-03-21 | 566 | 5.593648 | https://avatars.githubusercontent.com/u/3934254?v=4 | Main repository for Vispy | ['opengl', 'visualization'] | ['opengl', 'visualization'] | 2023-12-28 | [('holoviz/holoviz', 0.6010532379150391, 'viz', 0), ('maartenbreddels/ipyvolume', 0.5861509442329407, 'jupyter', 0), ('altair-viz/altair', 0.5802785158157349, 'viz', 1), ('holoviz/geoviews', 0.571336567401886, 'gis', 0), ('visgl/deck.gl', 0.5518122911453247, 'viz', 1), ('residentmario/geoplot', 0.5477085709571838, 'gis... | 192 | 8 | null | 2.87 | 40 | 23 | 132 | 1 | 4 | 3 | 4 | 40 | 169 | 90 | 4.2 | 51 |
1,650 | nlp | https://github.com/maartengr/keybert | [] | null | [] | [] | null | null | null | maartengr/keybert | KeyBERT | 3,034 | 317 | 33 | Python | https://MaartenGr.github.io/KeyBERT/ | Minimal keyword extraction with BERT | maartengr | 2024-01-14 | 2020-10-22 | 170 | 17.772385 | null | Minimal keyword extraction with BERT | ['bert', 'keyphrase-extraction', 'keyword-extraction', 'mmr'] | ['bert', 'keyphrase-extraction', 'keyword-extraction', 'mmr'] | 2024-01-03 | [('vi3k6i5/flashtext', 0.5377181768417358, 'data', 1), ('whu-zqh/chatgpt-vs.-bert', 0.529996395111084, 'llm', 1), ('jonasgeiping/cramming', 0.5119235515594482, 'nlp', 0), ('maartengr/bertopic', 0.5103285908699036, 'nlp', 1), ('paddlepaddle/paddlenlp', 0.5080262422561646, 'llm', 1)] | 9 | 8 | null | 0.15 | 19 | 9 | 39 | 0 | 1 | 3 | 1 | 19 | 60 | 90 | 3.2 | 51 |
837 | time-series | https://github.com/tdameritrade/stumpy | [] | null | [] | [] | null | null | null | tdameritrade/stumpy | stumpy | 2,896 | 274 | 54 | Python | https://stumpy.readthedocs.io/en/latest/ | STUMPY is a powerful and scalable Python library for modern time series analysis | tdameritrade | 2024-01-13 | 2019-05-03 | 247 | 11.697634 | https://avatars.githubusercontent.com/u/5022525?v=4 | STUMPY is a powerful and scalable Python library for modern time series analysis | ['anomaly-detection', 'dask', 'data-science', 'matrix-profile', 'motif-discovery', 'numba', 'pattern-matching', 'pydata', 'time-series-analysis', 'time-series-data-mining', 'time-series-segmentation'] | ['anomaly-detection', 'dask', 'data-science', 'matrix-profile', 'motif-discovery', 'numba', 'pattern-matching', 'pydata', 'time-series-analysis', 'time-series-data-mining', 'time-series-segmentation'] | 2024-01-12 | [('unit8co/darts', 0.7482045888900757, 'time-series', 2), ('alkaline-ml/pmdarima', 0.6753336787223816, 'time-series', 0), ('pycaret/pycaret', 0.6499117016792297, 'ml', 2), ('rjt1990/pyflux', 0.6353744268417358, 'time-series', 0), ('yzhao062/pyod', 0.6203436255455017, 'data', 2), ('firmai/atspy', 0.6093729138374329, 'ti... | 36 | 3 | null | 1.92 | 12 | 5 | 57 | 0 | 1 | 6 | 1 | 12 | 98 | 90 | 8.2 | 51 |
1,435 | llm | https://github.com/baichuan-inc/baichuan-13b | [] | null | [] | [] | null | null | null | baichuan-inc/baichuan-13b | Baichuan-13B | 2,867 | 218 | 31 | Python | https://huggingface.co/baichuan-inc/Baichuan-13B-Chat | A 13B large language model developed by Baichuan Intelligent Technology | baichuan-inc | 2024-01-13 | 2023-07-10 | 29 | 98.377451 | https://avatars.githubusercontent.com/u/136167093?v=4 | A 13B large language model developed by Baichuan Intelligent Technology | ['artificial-intelligence', 'benchmark', 'ceval', 'chatgpt', 'chinese', 'gpt-4', 'huggingface', 'large-language-models', 'mmlu', 'natural-language-processing'] | ['artificial-intelligence', 'benchmark', 'ceval', 'chatgpt', 'chinese', 'gpt-4', 'huggingface', 'large-language-models', 'mmlu', 'natural-language-processing'] | 2023-09-06 | [('lianjiatech/belle', 0.6785591840744019, 'llm', 0), ('hannibal046/awesome-llm', 0.6444519758224487, 'study', 0), ('freedomintelligence/llmzoo', 0.640003502368927, 'llm', 0), ('next-gpt/next-gpt', 0.6081295013427734, 'llm', 3), ('yueyu1030/attrprompt', 0.6001567840576172, 'llm', 2), ('ctlllll/llm-toolmaker', 0.5928089... | 6 | 3 | null | 0.62 | 23 | 6 | 6 | 4 | 0 | 0 | 0 | 23 | 19 | 90 | 0.8 | 51 |
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