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631 | debug | https://github.com/samuelcolvin/python-devtools | ['debug', 'print'] | null | [] | [] | null | null | null | samuelcolvin/python-devtools | python-devtools | 907 | 49 | 11 | Python | https://python-devtools.helpmanual.io/ | Dev tools for python | samuelcolvin | 2024-01-12 | 2017-08-20 | 336 | 2.697111 | null | Dev tools for python | ['devtools', 'python-devtools'] | ['debug', 'devtools', 'print', 'python-devtools'] | 2023-09-03 | [('alexmojaki/snoop', 0.7110832929611206, 'debug', 0), ('inducer/pudb', 0.6053194999694824, 'debug', 1), ('urwid/urwid', 0.5885550379753113, 'term', 0), ('amaargiru/pyroad', 0.5811712741851807, 'study', 0), ('pympler/pympler', 0.5581871271133423, 'perf', 0), ('nedbat/coveragepy', 0.5552131533622742, 'testing', 0), ('ga... | 12 | 5 | null | 0.37 | 8 | 1 | 78 | 4 | 4 | 3 | 4 | 8 | 13 | 90 | 1.6 | 33 |
394 | web | https://github.com/emmett-framework/emmett | [] | null | [] | [] | null | null | null | emmett-framework/emmett | emmett | 899 | 69 | 30 | Python | null | The web framework for inventors | emmett-framework | 2024-01-10 | 2014-10-20 | 484 | 1.85689 | https://avatars.githubusercontent.com/u/46401492?v=4 | The web framework for inventors | ['asgi', 'asyncio', 'emmett', 'web-framework'] | ['asgi', 'asyncio', 'emmett', 'web-framework'] | 2023-12-21 | [('django/django', 0.6188867688179016, 'web', 0), ('pallets/flask', 0.6101765632629395, 'web', 1), ('pallets/quart', 0.5764337778091431, 'web', 2), ('neoteroi/blacksheep', 0.5676200985908508, 'web', 2), ('klen/muffin', 0.56635981798172, 'web', 2), ('masoniteframework/masonite', 0.5554807186126709, 'web', 0), ('pylons/p... | 24 | 3 | null | 0.77 | 4 | 3 | 112 | 1 | 9 | 13 | 9 | 4 | 5 | 90 | 1.2 | 33 |
1,790 | web | https://github.com/feincms/feincms | ['cms'] | null | [] | [] | null | null | null | feincms/feincms | feincms | 878 | 230 | 39 | Python | http://www.feincms.org/ | A Django-based CMS with a focus on extensibility and concise code | feincms | 2024-01-13 | 2009-01-27 | 783 | 1.121328 | https://avatars.githubusercontent.com/u/935594?v=4 | A Django-based CMS with a focus on extensibility and concise code | [] | ['cms'] | 2023-12-22 | [('stephenmcd/mezzanine', 0.8132669925689697, 'web', 1), ('wagtail/wagtail', 0.7559544444084167, 'web', 1), ('django/django', 0.5812693238258362, 'web', 0), ('pylons/pyramid', 0.5519199371337891, 'web', 0), ('pallets/flask', 0.546400785446167, 'web', 0), ('bottlepy/bottle', 0.5126698613166809, 'web', 0), ('fastapi-admi... | 136 | 7 | null | 0.29 | 4 | 4 | 182 | 1 | 0 | 7 | 7 | 4 | 2 | 90 | 0.5 | 33 |
1,736 | viz | https://github.com/pydot/pydot | [] | null | [] | [] | null | null | null | pydot/pydot | pydot | 830 | 157 | 26 | Python | https://pypi.python.org/pypi/pydot | Python interface to Graphviz's Dot language | pydot | 2024-01-12 | 2015-04-13 | 459 | 1.807716 | https://avatars.githubusercontent.com/u/11192979?v=4 | Python interface to Graphviz's Dot language | ['dot-language', 'graphviz'] | ['dot-language', 'graphviz'] | 2023-12-30 | [('pygraphviz/pygraphviz', 0.7296152114868164, 'viz', 0), ('vmiklos/ged2dot', 0.5854193568229675, 'data', 0), ('plotly/plotly.py', 0.5558724403381348, 'viz', 0), ('westhealth/pyvis', 0.542072594165802, 'graph', 0), ('graphistry/pygraphistry', 0.5253562331199646, 'data', 0), ('dmlc/dgl', 0.5208896398544312, 'ml-dl', 0),... | 26 | 2 | null | 0.23 | 36 | 20 | 107 | 0 | 0 | 2 | 2 | 36 | 59 | 90 | 1.6 | 33 |
1,208 | ml | https://github.com/lmcinnes/pynndescent | [] | null | [] | [] | null | null | null | lmcinnes/pynndescent | pynndescent | 822 | 101 | 14 | Python | null | A Python nearest neighbor descent for approximate nearest neighbors | lmcinnes | 2024-01-12 | 2018-02-07 | 311 | 2.635822 | null | A Python nearest neighbor descent for approximate nearest neighbors | ['approximate-nearest-neighbor-search', 'knn-graphs', 'nearest-neighbor-search'] | ['approximate-nearest-neighbor-search', 'knn-graphs', 'nearest-neighbor-search'] | 2024-01-10 | [('spotify/voyager', 0.6540524363517761, 'ml', 1), ('nmslib/hnswlib', 0.6369488835334778, 'ml', 0), ('spotify/annoy', 0.6271777749061584, 'ml', 2), ('scikit-learn-contrib/metric-learn', 0.5760319828987122, 'ml', 0), ('qdrant/quaterion', 0.5621644854545593, 'ml', 1), ('criteo/autofaiss', 0.5459467172622681, 'ml', 0), ('... | 27 | 4 | null | 0.5 | 8 | 1 | 72 | 0 | 3 | 4 | 3 | 8 | 3 | 90 | 0.4 | 33 |
734 | data | https://github.com/koaning/human-learn | [] | null | [] | [] | null | null | null | koaning/human-learn | human-learn | 763 | 55 | 15 | Jupyter Notebook | https://koaning.github.io/human-learn/ | Natural Intelligence is still a pretty good idea. | koaning | 2024-01-11 | 2020-07-11 | 185 | 4.114792 | null | Natural Intelligence is still a pretty good idea. | ['benchmark', 'machine-learning', 'scikit-learn'] | ['benchmark', 'machine-learning', 'scikit-learn'] | 2024-01-02 | [('rasbt/machine-learning-book', 0.6072452068328857, 'study', 2), ('koaning/scikit-lego', 0.5959609150886536, 'ml', 2), ('automl/auto-sklearn', 0.5842374563217163, 'ml', 1), ('intel/scikit-learn-intelex', 0.5819746255874634, 'perf', 2), ('aiqc/aiqc', 0.5812904238700867, 'ml-ops', 0), ('tensorflow/tensorflow', 0.5748200... | 6 | 4 | null | 0.12 | 7 | 4 | 43 | 0 | 1 | 1 | 1 | 7 | 4 | 90 | 0.6 | 33 |
1,720 | util | https://github.com/asottile/reorder-python-imports | ['code-quality'] | null | [] | [] | null | null | null | asottile/reorder-python-imports | reorder-python-imports | 692 | 53 | 10 | Python | null | Rewrites source to reorder python imports | asottile | 2024-01-13 | 2015-01-01 | 473 | 1.460796 | null | Rewrites source to reorder python imports | ['linter', 'pre-commit', 'refactoring'] | ['code-quality', 'linter', 'pre-commit', 'refactoring'] | 2024-01-08 | [('pycqa/isort', 0.5951371192932129, 'util', 2), ('python-rope/rope', 0.5853264331817627, 'util', 1), ('facebookincubator/bowler', 0.5548760890960693, 'util', 1), ('tezromach/python-package-template', 0.5504276156425476, 'template', 0), ('dosisod/refurb', 0.5132452249526978, 'util', 0), ('hadialqattan/pycln', 0.5043818... | 18 | 5 | null | 0.73 | 8 | 8 | 110 | 0 | 0 | 7 | 7 | 8 | 3 | 90 | 0.4 | 33 |
1,862 | ml-rl | https://github.com/denys88/rl_games | [] | RL Games: High performance RL library | [] | [] | null | null | null | denys88/rl_games | rl_games | 626 | 107 | 18 | Jupyter Notebook | null | RL implementations | denys88 | 2024-01-14 | 2019-01-13 | 263 | 2.377645 | null | RL implementations | ['deep-learning', 'pytorch', 'reinforcement-learning'] | ['deep-learning', 'pytorch', 'reinforcement-learning'] | 2023-12-01 | [('thu-ml/tianshou', 0.7549825310707092, 'ml-rl', 1), ('pytorch/rl', 0.7474822402000427, 'ml-rl', 2), ('pytorch/ignite', 0.6810092926025391, 'ml-dl', 2), ('tensorlayer/tensorlayer', 0.6643456816673279, 'ml-rl', 2), ('keras-rl/keras-rl', 0.6609601974487305, 'ml-rl', 1), ('salesforce/warp-drive', 0.6500195264816284, 'ml-... | 14 | 4 | null | 0.42 | 18 | 12 | 61 | 1 | 2 | 2 | 2 | 18 | 24 | 90 | 1.3 | 33 |
1,594 | llm | https://github.com/continuum-llms/chatgpt-memory | [] | null | [] | [] | 1 | null | null | continuum-llms/chatgpt-memory | chatgpt-memory | 508 | 65 | 11 | Python | null | Allows to scale the ChatGPT API to multiple simultaneous sessions with infinite contextual and adaptive memory powered by GPT and Redis datastore. | continuum-llms | 2024-01-10 | 2023-03-12 | 46 | 10.975309 | https://avatars.githubusercontent.com/u/127662766?v=4 | Allows to scale the ChatGPT API to multiple simultaneous sessions with infinite contextual and adaptive memory powered by GPT and Redis datastore. | ['chatgpt', 'chatgpt-api', 'memory', 'redis'] | ['chatgpt', 'chatgpt-api', 'memory', 'redis'] | 2023-10-22 | [('run-llama/rags', 0.5546180605888367, 'llm', 1), ('openai/openai-cookbook', 0.5522615909576416, 'ml', 1), ('xtekky/gpt4free', 0.5107817053794861, 'llm', 2), ('zilliztech/gptcache', 0.5097682476043701, 'llm', 3), ('farizrahman4u/loopgpt', 0.5028600096702576, 'llm', 1)] | 2 | 1 | null | 2.1 | 4 | 4 | 10 | 3 | 0 | 0 | 0 | 4 | 6 | 90 | 1.5 | 33 |
253 | ml | https://github.com/amzn/pecos | [] | null | [] | [] | null | null | null | amzn/pecos | pecos | 478 | 103 | 20 | Python | https://libpecos.org/ | PECOS - Prediction for Enormous and Correlated Spaces | amzn | 2024-01-08 | 2020-08-12 | 180 | 2.64297 | https://avatars.githubusercontent.com/u/8594673?v=4 | PECOS - Prediction for Enormous and Correlated Spaces | ['approximate-nearest-neighbor-search', 'extreme-multi-label-classification', 'extreme-multi-label-ranking', 'machine-learning-algorithms', 'transformers'] | ['approximate-nearest-neighbor-search', 'extreme-multi-label-classification', 'extreme-multi-label-ranking', 'machine-learning-algorithms', 'transformers'] | 2024-01-06 | [('scikit-learn-contrib/lightning', 0.5417201519012451, 'ml', 0)] | 26 | 3 | null | 0.58 | 17 | 13 | 42 | 0 | 5 | 3 | 5 | 17 | 4 | 90 | 0.2 | 33 |
1,456 | util | https://github.com/conda/conda-pack | ['conda'] | null | [] | [] | null | null | null | conda/conda-pack | conda-pack | 459 | 82 | 27 | Python | https://conda.github.io/conda-pack/ | Package conda environments for redistribution | conda | 2024-01-12 | 2017-10-17 | 328 | 1.39939 | https://avatars.githubusercontent.com/u/6392739?v=4 | Package conda environments for redistribution | [] | ['conda'] | 2024-01-08 | [('mamba-org/quetz', 0.785363495349884, 'util', 1), ('conda/conda-build', 0.7299324870109558, 'util', 1), ('conda/constructor', 0.7213409543037415, 'util', 1), ('mamba-org/boa', 0.7062498927116394, 'util', 1), ('mamba-org/gator', 0.6601476073265076, 'jupyter', 1), ('mamba-org/mamba', 0.6462101340293884, 'util', 1), ('c... | 28 | 5 | null | 0.88 | 27 | 19 | 76 | 0 | 1 | 2 | 1 | 27 | 31 | 90 | 1.1 | 33 |
330 | ml | https://github.com/jacopotagliabue/reclist | [] | null | [] | [] | null | null | null | jacopotagliabue/reclist | reclist | 433 | 26 | 10 | Python | https://reclist.io | Behavioral "black-box" testing for recommender systems | jacopotagliabue | 2024-01-08 | 2021-11-08 | 116 | 3.728167 | https://avatars.githubusercontent.com/u/105445087?v=4 | Behavioral "black-box" testing for recommender systems | ['evaluation', 'machine-learning', 'machine-learning-library', 'qa-automation', 'recommender-system'] | ['evaluation', 'machine-learning', 'machine-learning-library', 'qa-automation', 'recommender-system'] | 2023-08-09 | [('nicolashug/surprise', 0.5908733010292053, 'ml', 1), ('microsoft/recommenders', 0.5187485218048096, 'study', 1)] | 10 | 2 | null | 1.37 | 1 | 0 | 27 | 5 | 0 | 3 | 3 | 1 | 4 | 90 | 4 | 33 |
581 | gis | https://github.com/pysal/momepy | [] | null | [] | [] | null | null | null | pysal/momepy | momepy | 420 | 54 | 20 | Python | https://docs.momepy.org | Urban Morphology Measuring Toolkit | pysal | 2024-01-14 | 2018-03-30 | 304 | 1.378987 | https://avatars.githubusercontent.com/u/3769919?v=4 | Urban Morphology Measuring Toolkit | ['morphological-analysis', 'morphology', 'morphometrics', 'urban', 'urban-morphometrics', 'urban-street-networks'] | ['morphological-analysis', 'morphology', 'morphometrics', 'urban', 'urban-morphometrics', 'urban-street-networks'] | 2024-01-12 | [('spatialucr/geosnap', 0.5846999287605286, 'gis', 0), ('mcordts/cityscapesscripts', 0.564961314201355, 'gis', 0), ('gboeing/street-network-models', 0.5618022680282593, 'sim', 0), ('udst/urbansim', 0.5606027245521545, 'sim', 0)] | 14 | 4 | null | 0.87 | 19 | 17 | 70 | 0 | 2 | 3 | 2 | 19 | 36 | 90 | 1.9 | 33 |
1,796 | llm | https://github.com/hazyresearch/manifest | ['prompt-engineering'] | null | [] | [] | null | null | null | hazyresearch/manifest | manifest | 420 | 45 | 22 | Python | null | Prompt programming with FMs. | hazyresearch | 2024-01-04 | 2022-05-21 | 88 | 4.749596 | https://avatars.githubusercontent.com/u/2165246?v=4 | Prompt programming with FMs. | [] | ['prompt-engineering'] | 2024-01-12 | [('microsoft/promptbase', 0.629546046257019, 'llm', 1), ('hazyresearch/ama_prompting', 0.5880966782569885, 'llm', 1), ('keirp/automatic_prompt_engineer', 0.5553961396217346, 'llm', 1), ('stanfordnlp/dspy', 0.5367062091827393, 'llm', 0), ('promptslab/promptify', 0.5325891971588135, 'nlp', 1)] | 9 | 3 | null | 0.83 | 4 | 2 | 20 | 0 | 7 | 6 | 7 | 4 | 1 | 90 | 0.2 | 33 |
678 | util | https://github.com/sciunto-org/python-bibtexparser | [] | null | [] | [] | null | null | null | sciunto-org/python-bibtexparser | python-bibtexparser | 405 | 168 | 21 | Python | https://bibtexparser.readthedocs.io | Bibtex parser for Python 3 | sciunto-org | 2024-01-11 | 2013-01-05 | 577 | 0.701385 | https://avatars.githubusercontent.com/u/8595754?v=4 | Bibtex parser for Python 3 | ['bibtex', 'bibtex-files', 'latex'] | ['bibtex', 'bibtex-files', 'latex'] | 2024-01-04 | [] | 51 | 5 | null | 0.96 | 28 | 22 | 134 | 0 | 4 | 2 | 4 | 28 | 37 | 90 | 1.3 | 33 |
1,420 | llm | https://github.com/likenneth/honest_llama | ['language-model'] | null | [] | [] | null | null | null | likenneth/honest_llama | honest_llama | 308 | 28 | 7 | Python | null | Inference-Time Intervention: Eliciting Truthful Answers from a Language Model | likenneth | 2024-01-11 | 2023-05-19 | 36 | 8.421875 | null | Inference-Time Intervention: Eliciting Truthful Answers from a Language Model | [] | ['language-model'] | 2023-12-29 | [('keirp/automatic_prompt_engineer', 0.5166599750518799, 'llm', 1), ('reasoning-machines/pal', 0.5100179314613342, 'llm', 1)] | 4 | 0 | null | 0.29 | 10 | 7 | 8 | 0 | 0 | 0 | 0 | 10 | 39 | 90 | 3.9 | 33 |
506 | data | https://github.com/facebookresearch/mephisto | [] | null | [] | [] | null | null | null | facebookresearch/mephisto | Mephisto | 288 | 72 | 16 | Python | https://mephisto.ai/ | A suite of tools for managing crowdsourcing tasks from the inception through to data packaging for research use. | facebookresearch | 2024-01-09 | 2019-08-19 | 232 | 1.240615 | https://avatars.githubusercontent.com/u/16943930?v=4 | A suite of tools for managing crowdsourcing tasks from the inception through to data packaging for research use. | [] | [] | 2023-12-27 | [] | 40 | 3 | null | 3.15 | 31 | 15 | 54 | 1 | 0 | 5 | 5 | 31 | 40 | 90 | 1.3 | 33 |
1,679 | util | https://github.com/hadialqattan/pycln | [] | null | [] | [] | null | null | null | hadialqattan/pycln | pycln | 282 | 17 | 3 | Python | https://hadialqattan.github.io/pycln | A formatter for finding and removing unused import statements. | hadialqattan | 2024-01-12 | 2020-08-14 | 180 | 1.561709 | null | A formatter for finding and removing unused import statements. | ['cli-app', 'cross-platform', 'formatters', 'linters', 'pycln', 'quality-assurance', 'unused-imports'] | ['cli-app', 'cross-platform', 'formatters', 'linters', 'pycln', 'quality-assurance', 'unused-imports'] | 2023-11-14 | [('pycqa/isort', 0.6549221277236938, 'util', 0), ('pycqa/autoflake', 0.6299516558647156, 'util', 0), ('landscapeio/prospector', 0.6040316224098206, 'util', 0), ('google/yapf', 0.5293893218040466, 'util', 0), ('dosisod/refurb', 0.5226925611495972, 'util', 0), ('kellyjonbrazil/jc', 0.5115851163864136, 'util', 0), ('psf/b... | 13 | 4 | null | 0.62 | 10 | 7 | 42 | 2 | 10 | 12 | 10 | 10 | 25 | 90 | 2.5 | 33 |
1,248 | util | https://github.com/steamship-core/python-client | [] | null | [] | [] | null | null | null | steamship-core/python-client | python-client | 280 | 52 | 9 | Python | null | null | steamship-core | 2024-01-06 | 2021-05-11 | 142 | 1.971831 | https://avatars.githubusercontent.com/u/99272373?v=4 | steamship-core/python-client | [] | [] | 2024-01-03 | [('replicate/replicate-python', 0.6438118815422058, 'ml', 0), ('steamship-core/steamship-langchain', 0.5675639510154724, 'util', 0), ('simple-salesforce/simple-salesforce', 0.5220065116882324, 'data', 0)] | 12 | 4 | null | 5.48 | 13 | 12 | 33 | 0 | 83 | 79 | 83 | 13 | 1 | 90 | 0.1 | 33 |
1,311 | util | https://github.com/rasahq/rasa-sdk | ['sdk', 'nlu'] | null | [] | [] | null | null | null | rasahq/rasa-sdk | rasa-sdk | 274 | 225 | 35 | Python | https://rasa.com/docs | SDK for the development of custom actions for Rasa | rasahq | 2024-01-12 | 2018-06-18 | 293 | 0.934698 | https://avatars.githubusercontent.com/u/21214473?v=4 | SDK for the development of custom actions for Rasa | [] | ['nlu', 'sdk'] | 2024-01-09 | [] | 99 | 4 | null | 2.12 | 35 | 30 | 68 | 0 | 23 | 21 | 23 | 35 | 12 | 90 | 0.3 | 33 |
444 | gis | https://github.com/pysal/spopt | [] | null | [] | [] | null | null | null | pysal/spopt | spopt | 233 | 40 | 13 | Python | https://pysal.org/spopt/ | Spatial Optimization | pysal | 2024-01-10 | 2019-03-01 | 256 | 0.908129 | https://avatars.githubusercontent.com/u/3769919?v=4 | Spatial Optimization | ['facility-location', 'location-allocation', 'location-modeling', 'regionalization', 'resource-planning', 'routing', 'spatial-analysis', 'spatial-optimization', 'transportation'] | ['facility-location', 'location-allocation', 'location-modeling', 'regionalization', 'resource-planning', 'routing', 'spatial-analysis', 'spatial-optimization', 'transportation'] | 2024-01-02 | [] | 18 | 5 | null | 1.25 | 38 | 33 | 59 | 0 | 3 | 3 | 3 | 39 | 63 | 90 | 1.6 | 33 |
567 | gis | https://github.com/developmentseed/geojson-pydantic | [] | null | [] | [] | null | null | null | developmentseed/geojson-pydantic | geojson-pydantic | 179 | 33 | 14 | Python | https://developmentseed.org/geojson-pydantic/ | Pydantic data models for the GeoJSON spec | developmentseed | 2024-01-09 | 2020-05-21 | 192 | 0.928836 | https://avatars.githubusercontent.com/u/92384?v=4 | Pydantic data models for the GeoJSON spec | ['geojson', 'geojson-spec', 'pydantic'] | ['geojson', 'geojson-spec', 'pydantic'] | 2023-12-20 | [('brokenloop/jsontopydantic', 0.7540448904037476, 'util', 0)] | 22 | 7 | null | 1.54 | 6 | 4 | 44 | 1 | 0 | 6 | 6 | 6 | 17 | 90 | 2.8 | 33 |
809 | util | https://github.com/aws-samples/sagemaker-ssh-helper | [] | null | [] | [] | null | null | null | aws-samples/sagemaker-ssh-helper | sagemaker-ssh-helper | 156 | 21 | 10 | Python | null | A helper library to connect into Amazon SageMaker with AWS Systems Manager and SSH (Secure Shell) | aws-samples | 2024-01-05 | 2022-10-14 | 67 | 2.308668 | https://avatars.githubusercontent.com/u/8931462?v=4 | A helper library to connect into Amazon SageMaker with AWS Systems Manager and SSH (Secure Shell) | ['amazon-sagemaker', 'aws', 'aws-systems-manager', 'machine-learning', 'pycharm', 'sagemaker', 'sagemaker-studio', 'ssh', 'vscode'] | ['amazon-sagemaker', 'aws', 'aws-systems-manager', 'machine-learning', 'pycharm', 'sagemaker', 'sagemaker-studio', 'ssh', 'vscode'] | 2023-08-28 | [('aws/sagemaker-python-sdk', 0.671806812286377, 'ml', 3), ('boto/boto3', 0.5350908637046814, 'util', 1), ('rhinosecuritylabs/pacu', 0.5007947087287903, 'security', 1)] | 6 | 3 | null | 4.25 | 7 | 4 | 15 | 5 | 10 | 11 | 10 | 7 | 22 | 90 | 3.1 | 33 |
97 | data | https://github.com/vi3k6i5/flashtext | [] | null | [] | [] | null | null | null | vi3k6i5/flashtext | flashtext | 5,496 | 610 | 140 | Python | null | Extract Keywords from sentence or Replace keywords in sentences. | vi3k6i5 | 2024-01-13 | 2017-08-15 | 337 | 16.308605 | null | Extract Keywords from sentence or Replace keywords in sentences. | ['data-extraction', 'keyword-extraction', 'nlp', 'search-in-text', 'word2vec'] | ['data-extraction', 'keyword-extraction', 'nlp', 'search-in-text', 'word2vec'] | 2020-05-03 | [('sloria/textblob', 0.5837533473968506, 'nlp', 1), ('nltk/nltk', 0.5405317544937134, 'nlp', 1), ('maartengr/keybert', 0.5377181768417358, 'nlp', 1)] | 7 | 1 | null | 0 | 7 | 1 | 78 | 45 | 0 | 0 | 0 | 7 | 4 | 90 | 0.6 | 32 |
21 | nlp | https://github.com/facebookresearch/drqa | ['question-answering'] | null | [] | [] | null | null | null | facebookresearch/drqa | DrQA | 4,431 | 920 | 160 | Python | null | Reading Wikipedia to Answer Open-Domain Questions | facebookresearch | 2024-01-12 | 2017-07-07 | 342 | 12.934529 | https://avatars.githubusercontent.com/u/16943930?v=4 | Reading Wikipedia to Answer Open-Domain Questions | [] | ['question-answering'] | 2021-05-18 | [('goldsmith/wikipedia', 0.5370073318481445, 'data', 0)] | 12 | 5 | null | 0 | 0 | 0 | 79 | 32 | 0 | 0 | 0 | 0 | 0 | 90 | 0 | 32 |
1,016 | debug | https://github.com/shobrook/rebound | [] | null | [] | [] | null | null | null | shobrook/rebound | rebound | 4,047 | 379 | 77 | Python | null | Command-line tool that instantly fetches Stack Overflow results when an exception is thrown | shobrook | 2024-01-12 | 2018-02-28 | 308 | 13.103145 | null | Command-line tool that instantly fetches Stack Overflow results when an exception is thrown | ['command-line-interface', 'command-line-tool', 'error-messages', 'stackoverflow', 'terminal-app'] | ['command-line-interface', 'command-line-tool', 'error-messages', 'stackoverflow', 'terminal-app'] | 2022-02-16 | [] | 16 | 2 | null | 0 | 0 | 0 | 72 | 23 | 0 | 1 | 1 | 0 | 0 | 90 | 0 | 32 |
999 | finance | https://github.com/cuemacro/finmarketpy | [] | null | [] | [] | null | null | null | cuemacro/finmarketpy | finmarketpy | 3,274 | 497 | 215 | Python | http://www.cuemacro.com | Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians) | cuemacro | 2024-01-13 | 2015-02-19 | 466 | 7.014998 | https://avatars.githubusercontent.com/u/20479975?v=4 | Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians) | ['backtesting-trading-strategies', 'trading-strategies'] | ['backtesting-trading-strategies', 'trading-strategies'] | 2024-01-01 | [('mementum/backtrader', 0.8932955265045166, 'finance', 0), ('gbeced/pyalgotrade', 0.7125941514968872, 'finance', 0), ('goldmansachs/gs-quant', 0.6932242512702942, 'finance', 1), ('kernc/backtesting.py', 0.6904587149620056, 'finance', 2), ('ta-lib/ta-lib-python', 0.6374157071113586, 'finance', 0), ('robcarver17/pysyste... | 14 | 1 | null | 0.08 | 0 | 0 | 108 | 0 | 2 | 2 | 2 | 0 | 0 | 90 | 0 | 32 |
1,155 | nlp | https://github.com/jsvine/markovify | [] | null | [] | [] | null | null | null | jsvine/markovify | markovify | 3,244 | 351 | 70 | Python | null | A simple, extensible Markov chain generator. | jsvine | 2024-01-13 | 2015-01-02 | 473 | 6.850075 | null | A simple, extensible Markov chain generator. | [] | [] | 2023-04-04 | [] | 62 | 2 | null | 0.12 | 0 | 0 | 110 | 9 | 0 | 4 | 4 | 0 | 0 | 90 | 0 | 32 |
1,129 | pandas | https://github.com/scikit-learn-contrib/sklearn-pandas | [] | null | [] | [] | null | null | null | scikit-learn-contrib/sklearn-pandas | sklearn-pandas | 2,768 | 420 | 94 | Python | null | Pandas integration with sklearn | scikit-learn-contrib | 2024-01-12 | 2013-04-22 | 562 | 4.924015 | https://avatars.githubusercontent.com/u/17349883?v=4 | Pandas integration with sklearn | [] | [] | 2022-07-17 | [('blaze/blaze', 0.626749575138092, 'pandas', 0), ('nalepae/pandarallel', 0.5978479981422424, 'pandas', 0), ('ddelange/mapply', 0.5479068756103516, 'pandas', 0), ('tkrabel/bamboolib', 0.5288722515106201, 'pandas', 0), ('lux-org/lux', 0.5287317037582397, 'viz', 0), ('adamerose/pandasgui', 0.5230746865272522, 'pandas', 0... | 39 | 4 | null | 0 | 1 | 1 | 131 | 18 | 0 | 1 | 1 | 1 | 1 | 90 | 1 | 32 |
1,481 | util | https://github.com/nschloe/tikzplotlib | [] | null | [] | [] | null | null | null | nschloe/tikzplotlib | tikzplotlib | 2,245 | 190 | 44 | Python | null | :bar_chart: Save matplotlib figures as TikZ/PGFplots for smooth integration into LaTeX. | nschloe | 2024-01-13 | 2010-01-14 | 732 | 3.06395 | null | 📊 Save matplotlib figures as TikZ/PGFplots for smooth integration into LaTeX. | ['latex', 'matplotlib', 'pgfplots', 'tikz'] | ['latex', 'matplotlib', 'pgfplots', 'tikz'] | 2022-02-28 | [('cuemacro/chartpy', 0.5781739354133606, 'viz', 1), ('matplotlib/matplotlib', 0.5151798725128174, 'viz', 1), ('holoviz/hvplot', 0.5042620897293091, 'pandas', 0)] | 61 | 3 | null | 0 | 6 | 1 | 170 | 23 | 0 | 6 | 6 | 6 | 7 | 90 | 1.2 | 32 |
476 | ml-dl | https://github.com/tensorflow/mesh | [] | null | [] | [] | null | null | null | tensorflow/mesh | mesh | 1,495 | 260 | 50 | Python | null | Mesh TensorFlow: Model Parallelism Made Easier | tensorflow | 2024-01-12 | 2018-09-20 | 279 | 5.34474 | https://avatars.githubusercontent.com/u/15658638?v=4 | Mesh TensorFlow: Model Parallelism Made Easier | [] | [] | 2023-11-17 | [('eleutherai/gpt-neo', 0.665690541267395, 'llm', 0), ('arogozhnikov/einops', 0.5747230052947998, 'ml-dl', 0), ('huggingface/accelerate', 0.5616391897201538, 'ml', 0), ('zacwellmer/worldmodels', 0.5606265068054199, 'ml-rl', 0), ('xl0/lovely-tensors', 0.5570968389511108, 'ml-dl', 0), ('ggerganov/ggml', 0.554904997348785... | 50 | 3 | null | 0.06 | 2 | 2 | 65 | 2 | 0 | 1 | 1 | 2 | 0 | 90 | 0 | 32 |
1,353 | study | https://github.com/atcold/nyu-dlsp21 | ['nyu', 'deep-learning'] | null | [] | [] | null | null | null | atcold/nyu-dlsp21 | NYU-DLSP21 | 1,477 | 271 | 51 | Jupyter Notebook | https://atcold.github.io/NYU-DLSP21/ | NYU Deep Learning Spring 2021 | atcold | 2024-01-12 | 2021-04-15 | 145 | 10.136275 | null | NYU Deep Learning Spring 2021 | ['deep-learning', 'ebm', 'nyu', 'yann-le-cunn'] | ['deep-learning', 'ebm', 'nyu', 'yann-le-cunn'] | 2023-10-04 | [('rasbt/stat453-deep-learning-ss20', 0.6361130475997925, 'study', 0), ('d2l-ai/d2l-en', 0.5323129296302795, 'study', 1), ('udacity/deep-learning-v2-pytorch', 0.5313364267349243, 'study', 1), ('udlbook/udlbook', 0.5171167850494385, 'study', 1)] | 22 | 3 | null | 0.15 | 0 | 0 | 33 | 3 | 0 | 0 | 0 | 0 | 0 | 90 | 0 | 32 |
109 | util | https://github.com/nficano/python-lambda | [] | null | [] | [] | null | null | null | nficano/python-lambda | python-lambda | 1,463 | 270 | 32 | Python | null | A toolkit for developing and deploying serverless Python code in AWS Lambda. | nficano | 2024-01-12 | 2016-02-26 | 413 | 3.537478 | null | A toolkit for developing and deploying serverless Python code in AWS Lambda. | ['aws', 'aws-lambda', 'microservices', 'serverless'] | ['aws', 'aws-lambda', 'microservices', 'serverless'] | 2022-06-03 | [('aws/chalice', 0.9045315980911255, 'web', 3), ('aws/aws-lambda-python-runtime-interface-client', 0.706771194934845, 'util', 0), ('geeogi/async-python-lambda-template', 0.6575234532356262, 'template', 0), ('jordaneremieff/mangum', 0.6575080752372742, 'web', 3), ('boto/boto3', 0.6395252346992493, 'util', 1), ('rpgreen/... | 48 | 5 | null | 0 | 1 | 0 | 96 | 20 | 0 | 7 | 7 | 1 | 1 | 90 | 1 | 32 |
890 | ml-ops | https://github.com/hi-primus/optimus | [] | null | [] | [] | null | null | null | hi-primus/optimus | optimus | 1,415 | 237 | 39 | Python | https://hi-optimus.com | :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark | hi-primus | 2024-01-13 | 2017-07-13 | 341 | 4.140886 | https://avatars.githubusercontent.com/u/86029697?v=4 | :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark | ['big-data-cleaning', 'bigdata', 'cudf', 'dask', 'dask-cudf', 'data-analysis', 'data-cleaner', 'data-cleaning', 'data-cleansing', 'data-exploration', 'data-extraction', 'data-preparation', 'data-profiling', 'data-science', 'data-transformation', 'data-wrangling', 'machine-learning', 'pyspark', 'spark'] | ['big-data-cleaning', 'bigdata', 'cudf', 'dask', 'dask-cudf', 'data-analysis', 'data-cleaner', 'data-cleaning', 'data-cleansing', 'data-exploration', 'data-extraction', 'data-preparation', 'data-profiling', 'data-science', 'data-transformation', 'data-wrangling', 'machine-learning', 'pyspark', 'spark'] | 2023-05-19 | [('ydataai/ydata-profiling', 0.6320505142211914, 'pandas', 5), ('rapidsai/cudf', 0.6309337019920349, 'pandas', 4), ('pyjanitor-devs/pyjanitor', 0.6122784614562988, 'pandas', 0), ('great-expectations/great_expectations', 0.6027732491493225, 'ml-ops', 2), ('mage-ai/mage-ai', 0.5950447916984558, 'ml-ops', 3), ('ploomber/p... | 24 | 5 | null | 0.06 | 8 | 5 | 79 | 8 | 1 | 22 | 1 | 8 | 5 | 90 | 0.6 | 32 |
413 | nlp | https://github.com/chrismattmann/tika-python | [] | null | [] | [] | null | null | null | chrismattmann/tika-python | tika-python | 1,373 | 273 | 39 | Python | null | Tika-Python is a Python binding to the Apache Tika™ REST services allowing Tika to be called natively in the Python community. | chrismattmann | 2024-01-12 | 2014-06-26 | 500 | 2.742083 | null | Tika-Python is a Python binding to the Apache Tika™ REST services allowing Tika to be called natively in the Python community. | ['buffer', 'covid-19', 'detection', 'extraction', 'memex', 'mime', 'nlp', 'nlp-library', 'nlp-machine-learning', 'parse', 'parser-interface', 'recognition', 'text-extraction', 'text-recognition', 'tika-python', 'tika-server', 'tika-server-jar', 'translation-interface', 'usc'] | ['buffer', 'covid-19', 'detection', 'extraction', 'memex', 'mime', 'nlp', 'nlp-library', 'nlp-machine-learning', 'parse', 'parser-interface', 'recognition', 'text-extraction', 'text-recognition', 'tika-python', 'tika-server', 'tika-server-jar', 'translation-interface', 'usc'] | 2023-08-11 | [('nuitka/nuitka', 0.5718207955360413, 'util', 0)] | 68 | 4 | null | 0.06 | 2 | 2 | 116 | 5 | 0 | 2 | 2 | 2 | 2 | 90 | 1 | 32 |
1,132 | ml | https://github.com/scikit-learn-contrib/metric-learn | [] | null | [] | [] | null | null | null | scikit-learn-contrib/metric-learn | metric-learn | 1,358 | 278 | 49 | Python | http://contrib.scikit-learn.org/metric-learn/ | Metric learning algorithms in Python | scikit-learn-contrib | 2024-01-12 | 2013-11-02 | 534 | 2.541032 | https://avatars.githubusercontent.com/u/17349883?v=4 | Metric learning algorithms in Python | ['machine-learning', 'metric-learning', 'scikit-learn'] | ['machine-learning', 'metric-learning', 'scikit-learn'] | 2023-09-29 | [('oml-team/open-metric-learning', 0.6861700415611267, 'ml', 1), ('scikit-learn/scikit-learn', 0.6777765154838562, 'ml', 1), ('scikit-learn-contrib/lightning', 0.6158003807067871, 'ml', 1), ('pycaret/pycaret', 0.6015337109565735, 'ml', 1), ('rasbt/mlxtend', 0.6002252101898193, 'ml', 1), ('kevinmusgrave/pytorch-metric-l... | 22 | 8 | null | 0.17 | 1 | 1 | 124 | 4 | 1 | 1 | 1 | 1 | 1 | 90 | 1 | 32 |
1,825 | util | https://github.com/aws-samples/aws-glue-samples | ['aws', 'glue'] | null | [] | [] | null | null | null | aws-samples/aws-glue-samples | aws-glue-samples | 1,349 | 771 | 76 | Python | null | AWS Glue code samples | aws-samples | 2024-01-08 | 2017-05-21 | 349 | 3.862168 | https://avatars.githubusercontent.com/u/8931462?v=4 | AWS Glue code samples | [] | ['aws', 'glue'] | 2023-10-18 | [] | 34 | 2 | null | 0.62 | 2 | 0 | 81 | 3 | 0 | 0 | 0 | 2 | 4 | 90 | 2 | 32 |
405 | perf | https://github.com/pympler/pympler | [] | null | [] | [] | null | null | null | pympler/pympler | pympler | 1,119 | 90 | 10 | Python | null | Development tool to measure, monitor and analyze the memory behavior of Python objects in a running Python application. | pympler | 2024-01-13 | 2012-10-04 | 590 | 1.894317 | https://avatars.githubusercontent.com/u/2490143?v=4 | Development tool to measure, monitor and analyze the memory behavior of Python objects in a running Python application. | [] | [] | 2022-07-24 | [('pythonprofilers/memory_profiler', 0.8423640131950378, 'profiling', 0), ('pythonspeed/filprofiler', 0.7303571105003357, 'profiling', 0), ('joblib/joblib', 0.6179777979850769, 'util', 0), ('eleutherai/pyfra', 0.6173771023750305, 'ml', 0), ('gaogaotiantian/viztracer', 0.6162266731262207, 'profiling', 0), ('landscapeio/... | 29 | 6 | null | 0 | 2 | 1 | 137 | 18 | 0 | 2 | 2 | 2 | 8 | 90 | 4 | 32 |
1,485 | util | https://github.com/python-injector/injector | ['dependency-injection'] | null | [] | [] | null | null | null | python-injector/injector | injector | 1,092 | 76 | 14 | Python | null | Python dependency injection framework, inspired by Guice | python-injector | 2024-01-14 | 2010-11-25 | 687 | 1.587869 | https://avatars.githubusercontent.com/u/119698538?v=4 | Python dependency injection framework, inspired by Guice | ['dependency-injection', 'dependency-injection-framework', 'di', 'injector'] | ['dependency-injection', 'dependency-injection-framework', 'di', 'injector'] | 2023-12-13 | [('ivankorobkov/python-inject', 0.7356547713279724, 'util', 1), ('allrod5/injectable', 0.6809417605400085, 'util', 1), ('ets-labs/python-dependency-injector', 0.6611223220825195, 'util', 2), ('proofit404/dependencies', 0.554645836353302, 'util', 1), ('mitsuhiko/rye', 0.5345786213874817, 'util', 0), ('indygreg/pyoxidize... | 29 | 3 | null | 0.38 | 9 | 6 | 160 | 1 | 0 | 4 | 4 | 8 | 10 | 90 | 1.2 | 32 |
721 | gis | https://github.com/geospatialpython/pyshp | [] | null | [] | [] | null | null | null | geospatialpython/pyshp | pyshp | 1,062 | 263 | 66 | Python | null | This library reads and writes ESRI Shapefiles in pure Python. | geospatialpython | 2024-01-09 | 2014-03-04 | 517 | 2.054159 | null | This library reads and writes ESRI Shapefiles in pure Python. | [] | [] | 2023-08-18 | [('imageio/imageio', 0.5908835530281067, 'util', 0), ('jorisschellekens/borb', 0.5256045460700989, 'util', 0), ('pytoolz/toolz', 0.5238029360771179, 'util', 0), ('julienpalard/pipe', 0.5082536935806274, 'util', 0)] | 42 | 5 | null | 0.04 | 1 | 0 | 120 | 5 | 0 | 2 | 2 | 1 | 2 | 90 | 2 | 32 |
1,728 | llm | https://github.com/rlancemartin/auto-evaluator | ['evaluation', 'question-answering'] | null | [] | [] | null | null | null | rlancemartin/auto-evaluator | auto-evaluator | 982 | 90 | 8 | Python | https://autoevaluator.langchain.com/ | Evaluation tool for LLM QA chains | rlancemartin | 2024-01-12 | 2023-04-14 | 41 | 23.621993 | null | Evaluation tool for LLM QA chains | [] | ['evaluation', 'question-answering'] | 2023-05-10 | [('night-chen/toolqa', 0.641534149646759, 'llm', 1), ('whitead/paper-qa', 0.5889334678649902, 'llm', 1), ('citadel-ai/langcheck', 0.5368258357048035, 'llm', 1), ('ibm/dromedary', 0.521746814250946, 'llm', 0), ('confident-ai/deepeval', 0.5153782963752747, 'testing', 1)] | 8 | 1 | null | 0.48 | 0 | 0 | 9 | 8 | 0 | 0 | 0 | 0 | 0 | 90 | 0 | 32 |
1,877 | math | https://github.com/cma-es/pycma | ['numerical-optimization'] | pycma is a Python implementation of CMA-ES and a few related numerical optimization tools. | [] | [] | null | null | null | cma-es/pycma | pycma | 979 | 170 | 17 | Python | null | Python implementation of CMA-ES | cma-es | 2024-01-09 | 2016-09-22 | 383 | 2.551378 | https://avatars.githubusercontent.com/u/9052298?v=4 | Python implementation of CMA-ES | [] | ['numerical-optimization'] | 2023-12-12 | [('scipy/scipy', 0.5867729187011719, 'math', 0), ('numpy/numpy', 0.5440859198570251, 'math', 0), ('scikit-optimize/scikit-optimize', 0.5281330943107605, 'ml', 0), ('stijnwoestenborghs/gradi-mojo', 0.5154417753219604, 'util', 0), ('pyomo/pyomo', 0.5060227513313293, 'math', 0)] | 13 | 2 | null | 1.37 | 30 | 20 | 89 | 1 | 1 | 2 | 1 | 30 | 27 | 90 | 0.9 | 32 |
1,677 | util | https://github.com/pycqa/autoflake | [] | null | [] | [] | null | null | null | pycqa/autoflake | autoflake | 833 | 79 | 14 | Python | https://pypi.org/project/autoflake/ | Removes unused imports and unused variables as reported by pyflakes | pycqa | 2024-01-12 | 2012-12-27 | 578 | 1.439398 | https://avatars.githubusercontent.com/u/8749848?v=4 | Removes unused imports and unused variables as reported by pyflakes | ['formatter', 'linter', 'pyflakes'] | ['formatter', 'linter', 'pyflakes'] | 2024-01-12 | [('hadialqattan/pycln', 0.6299516558647156, 'util', 0), ('pycqa/eradicate', 0.5524262189865112, 'util', 0)] | 38 | 5 | null | 1.5 | 8 | 8 | 134 | 0 | 6 | 5 | 6 | 8 | 0 | 90 | 0 | 32 |
1,567 | llm | https://github.com/cerebras/modelzoo | ['training'] | null | [] | [] | null | null | null | cerebras/modelzoo | modelzoo | 776 | 110 | 23 | Python | null | null | cerebras | 2024-01-13 | 2022-04-08 | 94 | 8.205438 | https://avatars.githubusercontent.com/u/19580083?v=4 | cerebras/modelzoo | [] | ['training'] | 2023-11-28 | [] | 4 | 1 | null | 0.29 | 12 | 8 | 22 | 2 | 0 | 4 | 4 | 12 | 1 | 90 | 0.1 | 32 |
1,479 | testing | https://github.com/nose-devs/nose2 | [] | null | [] | [] | null | null | null | nose-devs/nose2 | nose2 | 768 | 137 | 23 | Python | https://nose2.io | The successor to nose, based on unittest2 | nose-devs | 2024-01-10 | 2011-12-14 | 632 | 1.213544 | https://avatars.githubusercontent.com/u/1263082?v=4 | The successor to nose, based on unittest2 | ['nose', 'nose2', 'nosetest', 'nosetests', 'testing', 'testing-framework', 'testing-library', 'testing-tool', 'testing-tools', 'unit-test', 'unittest', 'unittesting'] | ['nose', 'nose2', 'nosetest', 'nosetests', 'testing', 'testing-framework', 'testing-library', 'testing-tool', 'testing-tools', 'unit-test', 'unittest', 'unittesting'] | 2023-12-25 | [] | 77 | 4 | null | 0.75 | 13 | 8 | 147 | 1 | 0 | 3 | 3 | 13 | 11 | 90 | 0.8 | 32 |
623 | gis | https://github.com/makepath/xarray-spatial | [] | null | [] | [] | null | null | null | makepath/xarray-spatial | xarray-spatial | 752 | 79 | 23 | Python | https://xarray-spatial.org | Raster-based Spatial Analytics for Python | makepath | 2024-01-04 | 2020-02-08 | 207 | 3.625344 | https://avatars.githubusercontent.com/u/60046102?v=4 | Raster-based Spatial Analytics for Python | ['datashader', 'numba', 'raster-analysis', 'spatial-analysis', 'xarray'] | ['datashader', 'numba', 'raster-analysis', 'spatial-analysis', 'xarray'] | 2023-07-10 | [('pysal/pysal', 0.6753366589546204, 'gis', 0), ('earthlab/earthpy', 0.6488336324691772, 'gis', 0), ('residentmario/geoplot', 0.59319007396698, 'gis', 1), ('toblerity/rtree', 0.5867227911949158, 'gis', 0), ('contextlab/hypertools', 0.5519405603408813, 'ml', 0), ('geopandas/geopandas', 0.5509017705917358, 'gis', 0), ('p... | 28 | 4 | null | 0.21 | 99 | 95 | 48 | 6 | 2 | 10 | 2 | 99 | 3 | 90 | 0 | 32 |
1,726 | util | https://github.com/urschrei/pyzotero | ['zotero'] | null | [] | [] | null | null | null | urschrei/pyzotero | pyzotero | 734 | 86 | 17 | Python | https://pyzotero.readthedocs.org | Pyzotero: a Python client for the Zotero API | urschrei | 2024-01-12 | 2011-02-28 | 674 | 1.08879 | null | Pyzotero: a Python client for the Zotero API | ['citations', 'digital-humanities', 'zotero'] | ['citations', 'digital-humanities', 'zotero'] | 2023-12-04 | [('goldsmith/wikipedia', 0.5380213856697083, 'data', 0), ('eleutherai/pyfra', 0.5244025588035583, 'ml', 0), ('scholarly-python-package/scholarly', 0.5180812478065491, 'data', 1), ('paperswithcode/galai', 0.5094993710517883, 'llm', 1)] | 27 | 8 | null | 0.69 | 6 | 4 | 157 | 1 | 11 | 11 | 11 | 6 | 3 | 90 | 0.5 | 32 |
679 | ml | https://github.com/nvidia/cuda-python | [] | null | [] | [] | null | null | null | nvidia/cuda-python | cuda-python | 689 | 90 | 30 | Python | https://nvidia.github.io/cuda-python/ | CUDA Python Low-level Bindings | nvidia | 2024-01-13 | 2021-06-28 | 135 | 5.098309 | https://avatars.githubusercontent.com/u/1728152?v=4 | CUDA Python Low-level Bindings | [] | [] | 2023-11-29 | [('pybind/pybind11', 0.6058850288391113, 'perf', 0), ('cupy/cupy', 0.5955917835235596, 'math', 0), ('pytorch/data', 0.5482061505317688, 'data', 0), ('numba/numba', 0.5387571454048157, 'perf', 0), ('rapidsai/cudf', 0.5373781323432922, 'pandas', 0), ('pytoolz/toolz', 0.5279120802879333, 'util', 0), ('marella/ctransformer... | 2 | 1 | null | 0.13 | 7 | 5 | 31 | 2 | 6 | 6 | 6 | 7 | 9 | 90 | 1.3 | 32 |
1,568 | ml | https://github.com/huggingface/exporters | ['coreml'] | null | [] | [] | null | null | null | huggingface/exporters | exporters | 484 | 29 | 23 | Python | null | Export Hugging Face models to Core ML and TensorFlow Lite | huggingface | 2024-01-10 | 2022-05-23 | 88 | 5.491086 | https://avatars.githubusercontent.com/u/25720743?v=4 | Export Hugging Face models to Core ML and TensorFlow Lite | ['coreml', 'coremltools', 'deep-learning', 'machine-learning', 'model-converter', 'pytorch', 'tensorflow', 'tflite', 'transformer'] | ['coreml', 'coremltools', 'deep-learning', 'machine-learning', 'model-converter', 'pytorch', 'tensorflow', 'tflite', 'transformer'] | 2023-11-22 | [('apple/coremltools', 0.6746289730072021, 'ml', 6), ('huggingface/huggingface_hub', 0.6611513495445251, 'ml', 3), ('huggingface/transformers', 0.618623673915863, 'nlp', 5), ('aws/sagemaker-python-sdk', 0.5837609171867371, 'ml', 3), ('lutzroeder/netron', 0.5719174742698669, 'ml', 5), ('huggingface/datasets', 0.56622678... | 6 | 3 | null | 0.79 | 14 | 8 | 20 | 2 | 0 | 0 | 0 | 14 | 12 | 90 | 0.9 | 32 |
1,253 | llm | https://github.com/hazyresearch/h3 | [] | null | [] | [] | null | null | null | hazyresearch/h3 | H3 | 472 | 54 | 32 | Assembly | null | Language Modeling with the H3 State Space Model | hazyresearch | 2024-01-05 | 2022-12-28 | 56 | 8.301508 | https://avatars.githubusercontent.com/u/2165246?v=4 | Language Modeling with the H3 State Space Model | [] | [] | 2023-09-29 | [('freedomintelligence/llmzoo', 0.5786004066467285, 'llm', 0), ('juncongmoo/pyllama', 0.567010223865509, 'llm', 0), ('ctlllll/llm-toolmaker', 0.5581068992614746, 'llm', 0), ('lvwerra/trl', 0.5428241491317749, 'llm', 0), ('yizhongw/self-instruct', 0.534803569316864, 'llm', 0), ('hannibal046/awesome-llm', 0.5333759784698... | 4 | 1 | null | 0.52 | 1 | 0 | 13 | 4 | 0 | 0 | 0 | 1 | 4 | 90 | 4 | 32 |
716 | perf | https://github.com/noxdafox/pebble | [] | null | [] | [] | null | null | null | noxdafox/pebble | pebble | 465 | 46 | 10 | Python | null | Multi threading and processing eye-candy. | noxdafox | 2024-01-13 | 2013-10-16 | 536 | 0.866152 | null | Multi threading and processing eye-candy. | ['asyncio', 'decorators', 'multiprocessing', 'pool', 'threading'] | ['asyncio', 'decorators', 'multiprocessing', 'pool', 'threading'] | 2023-12-26 | [('sumerc/yappi', 0.7094334959983826, 'profiling', 1), ('joblib/joblib', 0.6440830826759338, 'util', 2), ('agronholm/anyio', 0.6101366281509399, 'perf', 1), ('python-greenlet/greenlet', 0.6010660529136658, 'perf', 0), ('python-trio/trio', 0.5942329168319702, 'perf', 0), ('samuelcolvin/arq', 0.5885294675827026, 'data', ... | 15 | 5 | null | 0.42 | 3 | 3 | 125 | 1 | 3 | 2 | 3 | 3 | 9 | 90 | 3 | 32 |
49 | util | https://github.com/mozillazg/pypy | [] | null | [] | [] | null | null | null | mozillazg/pypy | pypy | 442 | 66 | 13 | Python | https://foss.heptapod.net/pypy/pypy | The unofficial GitHub mirror of PyPy (mirrored via https://github.com/mozillazg/job-mirror-hg-repos) | mozillazg | 2024-01-13 | 2015-08-03 | 443 | 0.997421 | null | The unofficial GitHub mirror of PyPy (mirrored via https://github.com/mozillazg/job-mirror-hg-repos) | ['github-mirror', 'pypy', 'read-only-repository', 'readonly', 'unofficial', 'unofficial-mirror'] | ['github-mirror', 'pypy', 'read-only-repository', 'readonly', 'unofficial', 'unofficial-mirror'] | 2023-12-25 | [('pypa/gh-action-pypi-publish', 0.6144118309020996, 'util', 0), ('pypi/warehouse', 0.5795431733131409, 'util', 0), ('fauxpilot/fauxpilot', 0.5119403004646301, 'llm', 0), ('yaml/pyyaml', 0.5088357329368591, 'util', 0)] | 374 | 2 | null | 4.33 | 5 | 1 | 103 | 1 | 0 | 22 | 22 | 5 | 2 | 90 | 0.4 | 32 |
1,205 | llm | https://github.com/kbressem/medalpaca | ['question-answering'] | null | [] | [] | null | null | null | kbressem/medalpaca | medAlpaca | 378 | 39 | 14 | Python | null | LLM finetuned for medical question answering | kbressem | 2024-01-13 | 2023-03-28 | 44 | 8.590909 | null | LLM finetuned for medical question answering | [] | ['question-answering'] | 2023-09-07 | [('epfllm/meditron', 0.5290087461471558, 'llm', 0)] | 6 | 4 | null | 1.46 | 5 | 0 | 10 | 4 | 0 | 0 | 0 | 5 | 3 | 90 | 0.6 | 32 |
519 | gis | https://github.com/pygeos/pygeos | [] | null | [] | [] | null | null | null | pygeos/pygeos | pygeos | 375 | 42 | 14 | Python | https://pygeos.readthedocs.io | Wraps GEOS geometry functions in numpy ufuncs. | pygeos | 2024-01-10 | 2019-06-10 | 242 | 1.548673 | https://avatars.githubusercontent.com/u/56478268?v=4 | Wraps GEOS geometry functions in numpy ufuncs. | [] | [] | 2022-12-14 | [] | 13 | 9 | null | 0 | 1 | 1 | 56 | 13 | 0 | 4 | 4 | 1 | 5 | 90 | 5 | 32 |
589 | gis | https://github.com/geopython/owslib | [] | null | [] | [] | null | null | null | geopython/owslib | OWSLib | 356 | 271 | 30 | Python | https://owslib.readthedocs.io | OWSLib is a Python package for client programming with Open Geospatial Consortium (OGC) web service (hence OWS) interface standards, and their related content models. | geopython | 2024-01-12 | 2012-01-13 | 628 | 0.566364 | https://avatars.githubusercontent.com/u/1855122?v=4 | OWSLib is a Python package for client programming with Open Geospatial Consortium (OGC) web service (hence OWS) interface standards, and their related content models. | ['ogc', 'ogcapi', 'ows'] | ['ogc', 'ogcapi', 'ows'] | 2023-12-18 | [] | 146 | 5 | null | 0.77 | 14 | 9 | 146 | 1 | 6 | 7 | 6 | 14 | 12 | 90 | 0.9 | 32 |
336 | util | https://github.com/mrabarnett/mrab-regex | [] | null | [] | [] | null | null | null | mrabarnett/mrab-regex | mrab-regex | 321 | 37 | 7 | C | null | null | mrabarnett | 2024-01-05 | 2020-11-02 | 169 | 1.897804 | null | mrabarnett/mrab-regex | [] | [] | 2023-12-24 | [] | 9 | 2 | null | 0.31 | 15 | 8 | 39 | 1 | 0 | 9 | 9 | 15 | 33 | 90 | 2.2 | 32 |
1,009 | finance | https://github.com/gbeced/basana | [] | null | [] | [] | null | null | null | gbeced/basana | basana | 292 | 33 | 13 | Python | null | A Python async and event driven framework for algorithmic trading, with a focus on crypto currencies. | gbeced | 2024-01-13 | 2023-03-04 | 47 | 6.156627 | null | A Python async and event driven framework for algorithmic trading, with a focus on crypto currencies. | ['algorithmic-trading', 'asyncio', 'backtesting', 'binance', 'cryptocurrency', 'trading-bot'] | ['algorithmic-trading', 'asyncio', 'backtesting', 'binance', 'cryptocurrency', 'trading-bot'] | 2024-01-07 | [('gbeced/pyalgotrade', 0.7055126428604126, 'finance', 0), ('quantopian/zipline', 0.6551344394683838, 'finance', 1), ('robcarver17/pysystemtrade', 0.6477593779563904, 'finance', 0), ('quantconnect/lean', 0.6268382668495178, 'finance', 1), ('freqtrade/freqtrade', 0.6232483983039856, 'crypto', 3), ('ccxt/ccxt', 0.6148871... | 5 | 0 | null | 2.46 | 1 | 1 | 11 | 0 | 0 | 12 | 12 | 1 | 1 | 90 | 1 | 32 |
489 | gis | https://github.com/cogeotiff/rio-cogeo | [] | null | [] | [] | null | null | null | cogeotiff/rio-cogeo | rio-cogeo | 275 | 34 | 44 | Python | https://cogeotiff.github.io/rio-cogeo/ | Cloud Optimized GeoTIFF creation and validation plugin for rasterio | cogeotiff | 2024-01-11 | 2018-03-09 | 307 | 0.894101 | https://avatars.githubusercontent.com/u/40065466?v=4 | Cloud Optimized GeoTIFF creation and validation plugin for rasterio | ['cog', 'cogeotiff', 'geotiff', 'rasterio', 'satellite'] | ['cog', 'cogeotiff', 'geotiff', 'rasterio', 'satellite'] | 2024-01-08 | [('cogeotiff/rio-tiler', 0.6072856783866882, 'gis', 4)] | 17 | 5 | null | 0.52 | 2 | 2 | 71 | 0 | 0 | 11 | 11 | 2 | 4 | 90 | 2 | 32 |
1,615 | data | https://github.com/github/innovationgraph | ['github', 'economy'] | null | [] | [] | null | null | null | github/innovationgraph | innovationgraph | 248 | 20 | 88 | Python | https://innovationgraph.github.com/ | GitHub Innovation Graph | github | 2024-01-10 | 2023-09-14 | 19 | 12.57971 | https://avatars.githubusercontent.com/u/9919?v=4 | GitHub Innovation Graph | ['data', 'github', 'open-data'] | ['data', 'economy', 'github', 'open-data'] | 2024-01-11 | [('fastai/ghapi', 0.5455352067947388, 'util', 1), ('zenodo/zenodo', 0.5064103007316589, 'util', 0)] | 3 | 1 | null | 0.12 | 4 | 3 | 4 | 0 | 2 | 6 | 2 | 4 | 0 | 90 | 0 | 32 |
851 | jupyter | https://github.com/jupyter/nbformat | [] | null | [] | [] | null | null | null | jupyter/nbformat | nbformat | 231 | 154 | 22 | Python | http://nbformat.readthedocs.io/ | Reference implementation of the Jupyter Notebook format | jupyter | 2024-01-09 | 2015-04-09 | 459 | 0.502486 | https://avatars.githubusercontent.com/u/7388996?v=4 | Reference implementation of the Jupyter Notebook format | [] | [] | 2024-01-02 | [('jupyter/nbconvert', 0.810336709022522, 'jupyter', 0), ('jupyter/notebook', 0.7493022680282593, 'jupyter', 0), ('cohere-ai/notebooks', 0.7138713598251343, 'llm', 0), ('jupyter-widgets/ipywidgets', 0.7056740522384644, 'jupyter', 0), ('jakevdp/pythondatasciencehandbook', 0.6972000598907471, 'study', 0), ('mwouts/jupyte... | 79 | 7 | null | 0.71 | 15 | 8 | 107 | 0 | 4 | 4 | 4 | 15 | 13 | 90 | 0.9 | 32 |
1,886 | llm | https://github.com/predibase/llm_distillation_playbook | ['llm-distillation'] | null | [] | [] | null | null | null | predibase/llm_distillation_playbook | llm_distillation_playbook | 214 | 13 | 5 | Jupyter Notebook | null | Practical best practices for distilling large language models. | predibase | 2024-01-14 | 2023-12-06 | 7 | 27.236364 | https://avatars.githubusercontent.com/u/75280641?v=4 | Practical best practices for distilling large language models. | [] | ['llm-distillation'] | 2024-01-08 | [('cg123/mergekit', 0.622988224029541, 'llm', 0), ('huawei-noah/pretrained-language-model', 0.5744475722312927, 'nlp', 0), ('artidoro/qlora', 0.5419549345970154, 'llm', 0), ('ctlllll/llm-toolmaker', 0.5375890731811523, 'llm', 0), ('mooler0410/llmspracticalguide', 0.5229454040527344, 'study', 0), ('salesforce/xgen', 0.5... | 2 | 0 | null | 0.71 | 4 | 4 | 1 | 0 | 0 | 0 | 0 | 4 | 0 | 90 | 0 | 32 |
560 | gis | https://github.com/geopandas/pyogrio | [] | null | [] | [] | null | null | null | geopandas/pyogrio | pyogrio | 209 | 14 | 10 | Python | https://pyogrio.readthedocs.io | Vectorized vector I/O using OGR | geopandas | 2024-01-04 | 2020-03-27 | 200 | 1.042023 | https://avatars.githubusercontent.com/u/8130715?v=4 | Vectorized vector I/O using OGR | [] | [] | 2024-01-11 | [] | 12 | 3 | null | 1.27 | 29 | 17 | 46 | 0 | 6 | 4 | 6 | 29 | 58 | 90 | 2 | 32 |
982 | sim | https://github.com/espressomd/espresso | [] | null | [] | [] | null | null | null | espressomd/espresso | espresso | 206 | 181 | 22 | C++ | https://espressomd.org | The ESPResSo package | espressomd | 2024-01-04 | 2011-03-25 | 670 | 0.307201 | https://avatars.githubusercontent.com/u/689837?v=4 | The ESPResSo package | ['c-plus-plus', 'lattice-boltzmann', 'molecular-dynamics', 'physics', 'scientific-computing', 'soft-matter'] | ['c-plus-plus', 'lattice-boltzmann', 'molecular-dynamics', 'physics', 'scientific-computing', 'soft-matter'] | 2024-01-08 | [('deepmodeling/deepmd-kit', 0.5804603695869446, 'sim', 1), ('rdkit/rdkit', 0.5796418786048889, 'sim', 1)] | 184 | 4 | null | 5.9 | 65 | 39 | 156 | 0 | 1 | 4 | 1 | 65 | 56 | 90 | 0.9 | 32 |
1,272 | perf | https://github.com/qdrant/vector-db-benchmark | [] | null | [] | [] | null | null | null | qdrant/vector-db-benchmark | vector-db-benchmark | 170 | 42 | 5 | Python | https://qdrant.tech/benchmarks/ | Framework for benchmarking vector search engines | qdrant | 2024-01-09 | 2022-07-12 | 81 | 2.098765 | https://avatars.githubusercontent.com/u/73504361?v=4 | Framework for benchmarking vector search engines | ['benchmark', 'vector-database', 'vector-search', 'vector-search-engine'] | ['benchmark', 'vector-database', 'vector-search', 'vector-search-engine'] | 2024-01-12 | [('qdrant/qdrant', 0.582831621170044, 'data', 3), ('qdrant/qdrant-client', 0.5792778134346008, 'util', 3), ('qdrant/qdrant-haystack', 0.5743999481201172, 'data', 0), ('klen/py-frameworks-bench', 0.5516537427902222, 'perf', 1), ('lancedb/lancedb', 0.5436363816261292, 'data', 1), ('facebookresearch/faiss', 0.526425063610... | 9 | 5 | null | 2.79 | 34 | 25 | 18 | 0 | 0 | 1 | 1 | 34 | 32 | 90 | 0.9 | 32 |
825 | pandas | https://github.com/blaze/blaze | [] | null | [] | [] | null | null | null | blaze/blaze | blaze | 3,178 | 393 | 195 | Python | blaze.pydata.org | NumPy and Pandas interface to Big Data | blaze | 2024-01-08 | 2012-10-26 | 587 | 5.408704 | https://avatars.githubusercontent.com/u/12833921?v=4 | NumPy and Pandas interface to Big Data | [] | [] | 2019-08-15 | [('nalepae/pandarallel', 0.6345915794372559, 'pandas', 0), ('scikit-learn-contrib/sklearn-pandas', 0.626749575138092, 'pandas', 0), ('vaexio/vaex', 0.6084710359573364, 'perf', 0), ('numpy/numpy', 0.6074309349060059, 'math', 0), ('pytables/pytables', 0.5941234230995178, 'data', 0), ('mwaskom/seaborn', 0.5715226531028748... | 67 | 6 | null | 0 | 1 | 1 | 137 | 54 | 0 | 4 | 4 | 1 | 0 | 90 | 0 | 31 |
1,441 | ml | https://github.com/hrnet/hrnet-semantic-segmentation | [] | null | [] | [] | null | null | null | hrnet/hrnet-semantic-segmentation | HRNet-Semantic-Segmentation | 3,006 | 681 | 56 | Python | null | The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919 | hrnet | 2024-01-11 | 2019-04-09 | 251 | 11.976096 | https://avatars.githubusercontent.com/u/49397099?v=4 | The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919 | ['cityscapes', 'high-resolution', 'high-resolution-net', 'hrnets', 'lip', 'pascal-context', 'segmentation', 'segmentation-transformer', 'semantic-segmentation', 'transformer'] | ['cityscapes', 'high-resolution', 'high-resolution-net', 'hrnets', 'lip', 'pascal-context', 'segmentation', 'segmentation-transformer', 'semantic-segmentation', 'transformer'] | 2021-05-04 | [('rapidai/rapidocr', 0.5680984258651733, 'data', 0), ('microsoft/swin-transformer', 0.5201693177223206, 'ml', 1), ('jaidedai/easyocr', 0.5142496824264526, 'data', 0), ('madmaze/pytesseract', 0.5132443308830261, 'data', 0)] | 8 | 1 | null | 0 | 4 | 0 | 58 | 33 | 0 | 0 | 0 | 4 | 5 | 90 | 1.2 | 31 |
993 | finance | https://github.com/quantopian/alphalens | [] | null | [] | [] | null | null | null | quantopian/alphalens | alphalens | 2,946 | 1,083 | 167 | Jupyter Notebook | http://quantopian.github.io/alphalens | Performance analysis of predictive (alpha) stock factors | quantopian | 2024-01-13 | 2016-06-03 | 399 | 7.3729 | https://avatars.githubusercontent.com/u/1393215?v=4 | Performance analysis of predictive (alpha) stock factors | ['algorithmic-trading', 'finance', 'jupyter', 'numpy', 'pandas'] | ['algorithmic-trading', 'finance', 'jupyter', 'numpy', 'pandas'] | 2020-04-27 | [('gbeced/pyalgotrade', 0.5202894806861877, 'finance', 0)] | 25 | 2 | null | 0 | 5 | 2 | 93 | 45 | 0 | 2 | 2 | 5 | 3 | 90 | 0.6 | 31 |
112 | ml | https://github.com/teamhg-memex/eli5 | [] | null | [] | [] | null | null | null | teamhg-memex/eli5 | eli5 | 2,705 | 332 | 66 | Jupyter Notebook | http://eli5.readthedocs.io | A library for debugging/inspecting machine learning classifiers and explaining their predictions | teamhg-memex | 2024-01-09 | 2016-09-15 | 384 | 7.031192 | https://avatars.githubusercontent.com/u/9270052?v=4 | A library for debugging/inspecting machine learning classifiers and explaining their predictions | ['crfsuite', 'data-science', 'explanation', 'inspection', 'lightgbm', 'machine-learning', 'nlp', 'scikit-learn', 'xgboost'] | ['crfsuite', 'data-science', 'explanation', 'inspection', 'lightgbm', 'machine-learning', 'nlp', 'scikit-learn', 'xgboost'] | 2020-01-22 | [('tensorflow/data-validation', 0.6825962066650391, 'ml-ops', 0), ('marcotcr/lime', 0.6452601552009583, 'ml-interpretability', 0), ('seldonio/alibi', 0.6379401683807373, 'ml-interpretability', 1), ('huggingface/evaluate', 0.6364562511444092, 'ml', 1), ('carla-recourse/carla', 0.6284937262535095, 'ml', 1), ('districtdat... | 14 | 6 | null | 0 | 1 | 1 | 89 | 48 | 0 | 4 | 4 | 1 | 0 | 90 | 0 | 31 |
175 | util | https://github.com/liiight/notifiers | [] | null | [] | [] | null | null | null | liiight/notifiers | notifiers | 2,564 | 100 | 30 | Python | http://notifiers.readthedocs.io/ | The easy way to send notifications | liiight | 2024-01-13 | 2017-06-01 | 347 | 7.37387 | null | The easy way to send notifications | ['notification-service', 'notifications', 'notifier'] | ['notification-service', 'notifications', 'notifier'] | 2022-07-14 | [('caronc/apprise', 0.6810635924339294, 'util', 3)] | 19 | 2 | null | 0 | 4 | 0 | 81 | 18 | 0 | 4 | 4 | 4 | 1 | 90 | 0.2 | 31 |
852 | jupyter | https://github.com/jupyter/nbviewer | [] | null | [] | [] | null | null | null | jupyter/nbviewer | nbviewer | 2,146 | 551 | 93 | Python | https://nbviewer.jupyter.org | nbconvert as a web service: Render Jupyter Notebooks as static web pages | jupyter | 2024-01-13 | 2012-08-05 | 599 | 3.58093 | https://avatars.githubusercontent.com/u/7388996?v=4 | nbconvert as a web service: Render Jupyter Notebooks as static web pages | ['jupyter', 'jupyter-notebook', 'nbconvert'] | ['jupyter', 'jupyter-notebook', 'nbconvert'] | 2023-01-27 | [('voila-dashboards/voila', 0.6448253989219666, 'jupyter', 2), ('jupyter-widgets/ipywidgets', 0.5482261180877686, 'jupyter', 0), ('jupyter/notebook', 0.547979474067688, 'jupyter', 2), ('jupyterlite/jupyterlite', 0.5257112979888916, 'jupyter', 1), ('vizzuhq/ipyvizzu', 0.5107673406600952, 'jupyter', 2), ('jupyter-widgets... | 96 | 5 | null | 0.04 | 6 | 1 | 139 | 12 | 0 | 0 | 0 | 6 | 4 | 90 | 0.7 | 31 |
586 | template | https://github.com/buuntu/fastapi-react | [] | null | [] | [] | null | null | null | buuntu/fastapi-react | fastapi-react | 1,945 | 315 | 41 | Python | null | 🚀 Cookiecutter Template for FastAPI + React Projects. Using PostgreSQL, SQLAlchemy, and Docker | buuntu | 2024-01-12 | 2020-03-21 | 201 | 9.656028 | null | 🚀 Cookiecutter Template for FastAPI + React Projects. Using PostgreSQL, SQLAlchemy, and Docker | ['boilerplate', 'cookiecutter', 'docker', 'fastapi', 'full-stack', 'jwt', 'nginx', 'oauth2', 'postgres', 'react', 'react-admin', 'sqlalchemy', 'typescript'] | ['boilerplate', 'cookiecutter', 'docker', 'fastapi', 'full-stack', 'jwt', 'nginx', 'oauth2', 'postgres', 'react', 'react-admin', 'sqlalchemy', 'typescript'] | 2022-02-18 | [('lyz-code/cookiecutter-python-project', 0.6677143573760986, 'template', 1), ('tedivm/robs_awesome_python_template', 0.6574198603630066, 'template', 0), ('ionelmc/cookiecutter-pylibrary', 0.6523356437683105, 'template', 1), ('cookiecutter/cookiecutter', 0.6335521340370178, 'template', 1), ('s3rius/fastapi-template', 0... | 13 | 5 | null | 0 | 0 | 0 | 46 | 23 | 0 | 1 | 1 | 0 | 0 | 90 | 0 | 31 |
987 | nlp | https://github.com/thudm/p-tuning-v2 | [] | null | [] | [] | null | null | null | thudm/p-tuning-v2 | P-tuning-v2 | 1,790 | 173 | 30 | Python | null | An optimized deep prompt tuning strategy comparable to fine-tuning across scales and tasks | thudm | 2024-01-13 | 2021-10-14 | 119 | 14.952267 | https://avatars.githubusercontent.com/u/48590610?v=4 | An optimized deep prompt tuning strategy comparable to fine-tuning across scales and tasks | ['natural-language-processing', 'p-tuning', 'parameter-efficient-learning', 'pretrained-language-model', 'prompt-tuning'] | ['natural-language-processing', 'p-tuning', 'parameter-efficient-learning', 'pretrained-language-model', 'prompt-tuning'] | 2023-10-20 | [('keirp/automatic_prompt_engineer', 0.6158888339996338, 'llm', 0), ('promptslab/awesome-prompt-engineering', 0.5705534815788269, 'study', 1), ('kyegomez/tree-of-thoughts', 0.5489909052848816, 'llm', 1), ('srush/minichain', 0.5268715620040894, 'llm', 0), ('microsoft/unilm', 0.5134304761886597, 'nlp', 0), ('ofa-sys/ofa'... | 3 | 1 | null | 0.04 | 7 | 0 | 27 | 3 | 0 | 0 | 0 | 7 | 1 | 90 | 0.1 | 31 |
608 | testing | https://github.com/teemu/pytest-sugar | [] | null | [] | [] | null | null | null | teemu/pytest-sugar | pytest-sugar | 1,189 | 70 | 18 | Python | null | a plugin for py.test that changes the default look and feel of py.test (e.g. progressbar, show tests that fail instantly) | teemu | 2024-01-13 | 2013-06-25 | 553 | 2.15009 | null | a plugin for py.test that changes the default look and feel of py.test (e.g. progressbar, show tests that fail instantly) | ['pytest', 'pytest-plugin', 'pytest-sugar', 'testing'] | ['pytest', 'pytest-plugin', 'pytest-sugar', 'testing'] | 2023-08-08 | [('pytest-dev/pytest-xdist', 0.6500891447067261, 'testing', 2), ('computationalmodelling/nbval', 0.6413612365722656, 'jupyter', 3), ('ionelmc/pytest-benchmark', 0.6360356211662292, 'testing', 1), ('samuelcolvin/pytest-pretty', 0.5765059590339661, 'testing', 1), ('pytest-dev/pytest-cov', 0.5729233622550964, 'testing', 1... | 50 | 7 | null | 0.27 | 1 | 0 | 128 | 5 | 1 | 1 | 1 | 1 | 1 | 90 | 1 | 31 |
883 | ml-dl | https://github.com/xl0/lovely-tensors | [] | null | [] | [] | null | null | null | xl0/lovely-tensors | lovely-tensors | 1,017 | 14 | 11 | Jupyter Notebook | https://xl0.github.io/lovely-tensors | Tensors, ready for human consumption | xl0 | 2024-01-13 | 2022-10-07 | 68 | 14.83125 | null | Tensors, ready for human consumption | ['deep-learning', 'pytorch', 'statistics', 'visualization'] | ['deep-learning', 'pytorch', 'statistics', 'visualization'] | 2023-04-27 | [('xl0/lovely-numpy', 0.7344928979873657, 'util', 3), ('ggerganov/ggml', 0.6742641925811768, 'ml', 0), ('pytorch/ignite', 0.6465728282928467, 'ml-dl', 2), ('keras-team/keras', 0.6338521242141724, 'ml-dl', 2), ('arogozhnikov/einops', 0.6286166310310364, 'ml-dl', 2), ('tensorly/tensorly', 0.61644446849823, 'ml-dl', 1), (... | 1 | 1 | null | 0.1 | 0 | 0 | 15 | 9 | 0 | 14 | 14 | 0 | 0 | 90 | 0 | 31 |
340 | term | https://github.com/jquast/blessed | [] | null | [] | [] | null | null | null | jquast/blessed | blessed | 999 | 69 | 26 | Python | http://pypi.python.org/pypi/blessed | Blessed is an easy, practical library for making python terminal apps | jquast | 2024-01-11 | 2014-03-01 | 517 | 1.930701 | null | Blessed is an easy, practical library for making python terminal apps | ['cli', 'curses', 'terminal'] | ['cli', 'curses', 'terminal'] | 2023-12-17 | [('urwid/urwid', 0.7145931720733643, 'term', 0), ('pygamelib/pygamelib', 0.6294499635696411, 'gamedev', 0), ('willmcgugan/rich', 0.6152134537696838, 'term', 1), ('tmbo/questionary', 0.6140781044960022, 'term', 1), ('hoffstadt/dearpygui', 0.6031554937362671, 'gui', 0), ('pypy/pypy', 0.6016967296600342, 'util', 0), ('goo... | 26 | 3 | null | 0.42 | 9 | 6 | 120 | 1 | 1 | 5 | 1 | 9 | 10 | 90 | 1.1 | 31 |
1,667 | util | https://github.com/requests/toolbelt | [] | null | [] | [] | null | null | null | requests/toolbelt | toolbelt | 966 | 184 | 21 | Python | https://toolbelt.readthedocs.org | A toolbelt of useful classes and functions to be used with python-requests | requests | 2024-01-12 | 2013-12-29 | 526 | 1.835505 | https://avatars.githubusercontent.com/u/2805331?v=4 | A toolbelt of useful classes and functions to be used with python-requests | ['http', 'python-requests', 'toolbox'] | ['http', 'python-requests', 'toolbox'] | 2023-10-12 | [('psf/requests', 0.7315183281898499, 'web', 2), ('getsentry/responses', 0.7001904249191284, 'testing', 0), ('encode/httpx', 0.6686779856681824, 'web', 1), ('falconry/falcon', 0.6299983263015747, 'web', 1), ('simple-salesforce/simple-salesforce', 0.610306441783905, 'data', 0), ('eleutherai/pyfra', 0.6041449308395386, '... | 69 | 6 | null | 0.15 | 6 | 2 | 122 | 3 | 0 | 2 | 2 | 6 | 3 | 90 | 0.5 | 31 |
1,406 | llm | https://github.com/ctlllll/llm-toolmaker | ['language-model'] | Large Language Models as Tool Makers | [] | [] | null | null | null | ctlllll/llm-toolmaker | LLM-ToolMaker | 961 | 94 | 16 | Jupyter Notebook | null | null | ctlllll | 2024-01-12 | 2023-05-25 | 35 | 26.908 | null | Large Language Models as Tool Makers | [] | ['language-model'] | 2023-05-29 | [('conceptofmind/toolformer', 0.7394540309906006, 'llm', 1), ('hannibal046/awesome-llm', 0.708982527256012, 'study', 1), ('keirp/automatic_prompt_engineer', 0.699556291103363, 'llm', 1), ('ai21labs/lm-evaluation', 0.6955636143684387, 'llm', 1), ('lianjiatech/belle', 0.6910099983215332, 'llm', 0), ('guidance-ai/guidance... | 1 | 1 | null | 0.06 | 2 | 0 | 8 | 8 | 0 | 0 | 0 | 2 | 0 | 90 | 0 | 31 |
488 | viz | https://github.com/luispedro/mahotas | [] | null | [] | [] | null | null | null | luispedro/mahotas | mahotas | 816 | 155 | 50 | Python | https://mahotas.rtfd.io | Computer Vision in Python | luispedro | 2024-01-12 | 2010-01-31 | 730 | 1.117371 | null | Computer Vision in Python | ['c-plus-plus', 'computer-vision', 'numpy'] | ['c-plus-plus', 'computer-vision', 'numpy'] | 2024-01-08 | [('scikit-image/scikit-image', 0.6524010300636292, 'util', 1), ('xl0/lovely-numpy', 0.5749441981315613, 'util', 1), ('google/jax', 0.5661518573760986, 'ml', 1), ('mdbloice/augmentor', 0.5612508654594421, 'ml', 0), ('numpy/numpy', 0.5569568872451782, 'math', 1), ('roboflow/supervision', 0.5504482388496399, 'ml', 1), ('p... | 34 | 5 | null | 0.15 | 1 | 0 | 170 | 0 | 0 | 4 | 4 | 1 | 1 | 90 | 1 | 31 |
18 | nlp | https://github.com/explosion/spacy-streamlit | [] | null | [] | [] | null | null | null | explosion/spacy-streamlit | spacy-streamlit | 734 | 113 | 20 | Python | https://share.streamlit.io/ines/spacy-streamlit-demo/master/app.py | 👑 spaCy building blocks and visualizers for Streamlit apps | explosion | 2024-01-10 | 2020-06-23 | 188 | 3.904255 | https://avatars.githubusercontent.com/u/20011530?v=4 | 👑 spaCy building blocks and visualizers for Streamlit apps | ['dependency-parsing', 'machine-learning', 'named-entity-recognition', 'natural-language-processing', 'ner', 'nlp', 'part-of-speech-tagging', 'spacy', 'streamlit', 'text-classification', 'tokenization', 'visualizer', 'visualizers', 'word-vectors'] | ['dependency-parsing', 'machine-learning', 'named-entity-recognition', 'natural-language-processing', 'ner', 'nlp', 'part-of-speech-tagging', 'spacy', 'streamlit', 'text-classification', 'tokenization', 'visualizer', 'visualizers', 'word-vectors'] | 2023-08-02 | [('streamlit/streamlit', 0.6851550340652466, 'viz', 2), ('explosion/spacy-models', 0.6529020071029663, 'nlp', 4), ('alphasecio/langchain-examples', 0.6193504929542542, 'llm', 1), ('explosion/spacy-transformers', 0.5857328772544861, 'llm', 4), ('sloria/textblob', 0.5445199012756348, 'nlp', 2), ('explosion/spacy-stanza',... | 14 | 5 | null | 0.1 | 1 | 0 | 43 | 6 | 2 | 4 | 2 | 1 | 1 | 90 | 1 | 31 |
1,408 | llm | https://github.com/salesforce/xgen | [] | null | [] | [] | null | null | null | salesforce/xgen | xgen | 695 | 35 | 12 | Python | null | Salesforce open-source LLMs with 8k sequence length. | salesforce | 2024-01-12 | 2023-06-23 | 31 | 22.013575 | https://avatars.githubusercontent.com/u/453694?v=4 | Salesforce open-source LLMs with 8k sequence length. | ['language-model', 'large-language-models', 'llm', 'nlp'] | ['language-model', 'large-language-models', 'llm', 'nlp'] | 2023-10-16 | [('eugeneyan/open-llms', 0.6812090873718262, 'study', 2), ('young-geng/easylm', 0.6715541481971741, 'llm', 2), ('mooler0410/llmspracticalguide', 0.6607375741004944, 'study', 2), ('eleutherai/the-pile', 0.6535871624946594, 'data', 1), ('explosion/spacy-llm', 0.6350138187408447, 'llm', 3), ('cg123/mergekit', 0.6309936046... | 2 | 0 | null | 0.67 | 2 | 1 | 7 | 3 | 0 | 0 | 0 | 2 | 1 | 90 | 0.5 | 31 |
875 | time-series | https://github.com/autoviml/auto_ts | [] | null | [] | [] | null | null | null | autoviml/auto_ts | Auto_TS | 655 | 106 | 17 | Jupyter Notebook | null | Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows. | autoviml | 2024-01-13 | 2020-02-15 | 206 | 3.17301 | null | Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows. | ['arima', 'auto-arima', 'auto-sklearn', 'auto-timeseries', 'autokeras', 'automl', 'autosklearn', 'prophet', 'sklearn', 'time-series', 'time-series-analysis', 'tpot'] | ['arima', 'auto-arima', 'auto-sklearn', 'auto-timeseries', 'autokeras', 'automl', 'autosklearn', 'prophet', 'sklearn', 'time-series', 'time-series-analysis', 'tpot'] | 2023-12-03 | [('dask/dask-ml', 0.5662448406219482, 'ml', 0), ('nixtla/statsforecast', 0.5572653412818909, 'time-series', 4), ('winedarksea/autots', 0.5450201034545898, 'time-series', 2), ('microsoft/flaml', 0.5320088863372803, 'ml', 1), ('alkaline-ml/pmdarima', 0.5241935849189758, 'time-series', 2), ('dask/distributed', 0.523719549... | 11 | 3 | null | 0.31 | 5 | 5 | 48 | 1 | 0 | 1 | 1 | 5 | 6 | 90 | 1.2 | 31 |
1,151 | util | https://github.com/erdewit/nest_asyncio | [] | null | [] | [] | null | null | null | erdewit/nest_asyncio | nest_asyncio | 599 | 54 | 17 | Python | null | Patch asyncio to allow nested event loops | erdewit | 2024-01-13 | 2018-09-07 | 281 | 2.127347 | null | Patch asyncio to allow nested event loops | ['asyncio', 'event-loop', 'nested', 'recursive'] | ['asyncio', 'event-loop', 'nested', 'recursive'] | 2023-11-27 | [('magicstack/uvloop', 0.6544142365455627, 'util', 2), ('alex-sherman/unsync', 0.597553551197052, 'util', 0), ('pytest-dev/pytest-asyncio', 0.5122057199478149, 'testing', 1)] | 12 | 4 | null | 0.19 | 3 | 3 | 65 | 2 | 1 | 2 | 1 | 3 | 7 | 90 | 2.3 | 31 |
667 | perf | https://github.com/brandtbucher/specialist | ['cpython'] | null | [] | [] | null | null | null | brandtbucher/specialist | specialist | 596 | 10 | 9 | Python | null | Visualize CPython 3.11's specializing, adaptive interpreter. :fire: | brandtbucher | 2024-01-14 | 2022-06-01 | 86 | 6.861842 | null | Visualize CPython 3.11's specializing, adaptive interpreter. 🔥 | [] | ['cpython'] | 2023-08-06 | [('python/cpython', 0.7123744487762451, 'util', 1), ('faster-cpython/ideas', 0.6769110560417175, 'perf', 1), ('faster-cpython/tools', 0.6422561407089233, 'perf', 1), ('p403n1x87/austin', 0.5802419185638428, 'profiling', 0), ('markshannon/faster-cpython', 0.5744246244430542, 'perf', 0), ('ipython/ipyparallel', 0.5722348... | 3 | 2 | null | 0.29 | 1 | 1 | 20 | 5 | 3 | 8 | 3 | 1 | 1 | 90 | 1 | 31 |
477 | gis | https://github.com/holoviz/geoviews | [] | null | [] | [] | null | null | null | holoviz/geoviews | geoviews | 546 | 73 | 25 | Python | http://geoviews.org | Simple, concise geographical visualization in Python | holoviz | 2024-01-11 | 2016-04-19 | 406 | 1.344828 | https://avatars.githubusercontent.com/u/51678735?v=4 | Simple, concise geographical visualization in Python | ['cartopy', 'geographic-visualizations', 'geoviews', 'holoviews', 'holoviz', 'plotting'] | ['cartopy', 'geographic-visualizations', 'geoviews', 'holoviews', 'holoviz', 'plotting'] | 2023-12-22 | [('holoviz/holoviz', 0.7218708992004395, 'viz', 3), ('scitools/cartopy', 0.7182220220565796, 'gis', 1), ('residentmario/geoplot', 0.6962321400642395, 'gis', 0), ('raphaelquast/eomaps', 0.6664366126060486, 'gis', 2), ('artelys/geonetworkx', 0.663130521774292, 'gis', 0), ('holoviz/holoviews', 0.6530880331993103, 'viz', 3... | 30 | 3 | null | 1.31 | 35 | 29 | 94 | 1 | 4 | 11 | 4 | 35 | 13 | 90 | 0.4 | 31 |
906 | ml | https://github.com/cvxgrp/pymde | [] | null | [] | [] | null | null | null | cvxgrp/pymde | pymde | 501 | 27 | 9 | Python | https://pymde.org | Minimum-distortion embedding with PyTorch | cvxgrp | 2024-01-09 | 2020-11-29 | 165 | 3.031115 | https://avatars.githubusercontent.com/u/2957335?v=4 | Minimum-distortion embedding with PyTorch | ['cuda', 'dimensionality-reduction', 'embedding', 'feature-vectors', 'gpu', 'graph-embedding', 'machine-learning', 'pytorch', 'visualization'] | ['cuda', 'dimensionality-reduction', 'embedding', 'feature-vectors', 'gpu', 'graph-embedding', 'machine-learning', 'pytorch', 'visualization'] | 2023-07-01 | [('pyg-team/pytorch_geometric', 0.6165646910667419, 'ml-dl', 1), ('koaning/embetter', 0.6085571646690369, 'data', 0), ('blackhc/toma', 0.588315486907959, 'ml-dl', 3), ('graphistry/pygraphistry', 0.5851930379867554, 'data', 2), ('xl0/lovely-tensors', 0.5830146074295044, 'ml-dl', 2), ('pytorch/torchrec', 0.56921076774597... | 10 | 7 | null | 0.04 | 1 | 0 | 38 | 7 | 0 | 6 | 6 | 1 | 1 | 90 | 1 | 31 |
937 | web | https://github.com/aeternalis-ingenium/fastapi-backend-template | [] | null | [] | [] | null | null | null | aeternalis-ingenium/fastapi-backend-template | FastAPI-Backend-Template | 486 | 76 | 10 | Python | null | A backend project template with FastAPI, PostgreSQL with asynchronous SQLAlchemy 2.0, Alembic for asynchronous database migration, and Docker. | aeternalis-ingenium | 2024-01-12 | 2022-12-05 | 60 | 8.08076 | null | A backend project template with FastAPI, PostgreSQL with asynchronous SQLAlchemy 2.0, Alembic for asynchronous database migration, and Docker. | ['alembic', 'asynchronous', 'asyncpg', 'codecov', 'coverage', 'docker', 'docker-compose', 'fastapi', 'githubactions', 'jwt', 'postgresql', 'pre-commit', 'pytest', 'sqlalchemy'] | ['alembic', 'asynchronous', 'asyncpg', 'codecov', 'coverage', 'docker', 'docker-compose', 'fastapi', 'githubactions', 'jwt', 'postgresql', 'pre-commit', 'pytest', 'sqlalchemy'] | 2023-12-13 | [('rawheel/fastapi-boilerplate', 0.7447752356529236, 'web', 6), ('tiangolo/full-stack-fastapi-postgresql', 0.6168069839477539, 'template', 4), ('aminalaee/sqladmin', 0.6071468591690063, 'data', 2), ('s3rius/fastapi-template', 0.5711674690246582, 'web', 3), ('sqlalchemy/alembic', 0.5487288236618042, 'data', 1), ('coller... | 7 | 3 | null | 0.27 | 11 | 5 | 14 | 1 | 0 | 0 | 0 | 11 | 1 | 90 | 0.1 | 31 |
1,389 | util | https://github.com/pycqa/docformatter | ['pep257'] | null | [] | [] | null | null | null | pycqa/docformatter | docformatter | 478 | 57 | 9 | Python | https://pypi.python.org/pypi/docformatter | Formats docstrings to follow PEP 257 | pycqa | 2024-01-07 | 2012-05-26 | 609 | 0.784341 | https://avatars.githubusercontent.com/u/8749848?v=4 | Formats docstrings to follow PEP 257 | ['autoformat', 'docstring', 'formatter'] | ['autoformat', 'docstring', 'formatter', 'pep257'] | 2023-10-15 | [('danielnoord/pydocstringformatter', 0.8163774013519287, 'util', 2), ('hhatto/autopep8', 0.591210126876831, 'util', 1), ('mkdocstrings/mkdocstrings', 0.5333818793296814, 'util', 0), ('mkdocstrings/python', 0.503516674041748, 'util', 0)] | 30 | 4 | null | 1.31 | 12 | 3 | 142 | 3 | 12 | 5 | 12 | 12 | 19 | 90 | 1.6 | 31 |
1,772 | jupyter | https://github.com/bloomberg/ipydatagrid | [] | null | [] | [] | null | null | null | bloomberg/ipydatagrid | ipydatagrid | 467 | 47 | 16 | TypeScript | null | Fast Datagrid widget for the Jupyter Notebook and JupyterLab | bloomberg | 2024-01-12 | 2019-07-19 | 236 | 1.974034 | https://avatars.githubusercontent.com/u/1416818?v=4 | Fast Datagrid widget for the Jupyter Notebook and JupyterLab | ['datagrid', 'datatable', 'grid', 'jupyter-notebooks', 'jupyterlab-extension'] | ['datagrid', 'datatable', 'grid', 'jupyter-notebooks', 'jupyterlab-extension'] | 2023-12-09 | [('jupyter-widgets/ipywidgets', 0.6741766929626465, 'jupyter', 2), ('quantopian/qgrid', 0.6440353989601135, 'jupyter', 0), ('tkrabel/bamboolib', 0.6406834721565247, 'pandas', 0), ('aws/graph-notebook', 0.5870513916015625, 'jupyter', 0), ('jupyterlab/jupyterlab-desktop', 0.5657516717910767, 'jupyter', 0), ('jupyter/note... | 19 | 4 | null | 1.12 | 17 | 7 | 55 | 3 | 4 | 9 | 4 | 17 | 12 | 90 | 0.7 | 31 |
740 | study | https://github.com/bayesianmodelingandcomputationinpython/bookcode_edition1 | [] | null | [] | [] | null | null | null | bayesianmodelingandcomputationinpython/bookcode_edition1 | BookCode_Edition1 | 456 | 120 | 18 | Jupyter Notebook | https://www.bayesiancomputationbook.com | null | bayesianmodelingandcomputationinpython | 2024-01-13 | 2021-08-17 | 128 | 3.5625 | https://avatars.githubusercontent.com/u/84690770?v=4 | bayesianmodelingandcomputationinpython/BookCode_Edition1 | [] | [] | 2023-12-28 | [('pymc-devs/pymc3', 0.6229053735733032, 'ml', 0), ('gerdm/prml', 0.5888375639915466, 'study', 0), ('pytorch/botorch', 0.5796522498130798, 'ml-dl', 0), ('probml/pyprobml', 0.5301855802536011, 'ml', 0), ('pyro-ppl/pyro', 0.5214691162109375, 'ml-dl', 0), ('scikit-optimize/scikit-optimize', 0.5192668437957764, 'ml', 0)] | 10 | 4 | null | 0.19 | 9 | 6 | 29 | 1 | 0 | 0 | 0 | 9 | 12 | 90 | 1.3 | 31 |
1,629 | data | https://github.com/databrickslabs/dbx | [] | null | [] | [] | null | null | null | databrickslabs/dbx | dbx | 411 | 114 | 21 | Python | https://dbx.readthedocs.io | 🧱 Databricks CLI eXtensions - aka dbx is a CLI tool for development and advanced Databricks workflows management. | databrickslabs | 2024-01-04 | 2020-03-03 | 204 | 2.014706 | https://avatars.githubusercontent.com/u/49501376?v=4 | 🧱 Databricks CLI eXtensions - aka dbx is a CLI tool for development and advanced Databricks workflows management. | ['ci', 'cicd', 'databricks', 'databricks-api', 'databricks-cli', 'mlops'] | ['ci', 'cicd', 'databricks', 'databricks-api', 'databricks-cli', 'mlops'] | 2023-09-19 | [('databricks/dbt-databricks', 0.6466124057769775, 'data', 1), ('hyperqueryhq/whale', 0.5740757584571838, 'data', 0), ('dagster-io/dagster', 0.5274744033813477, 'ml-ops', 1), ('airbytehq/airbyte', 0.5199562907218933, 'data', 0), ('mage-ai/mage-ai', 0.5128315091133118, 'ml-ops', 0), ('airbnb/omniduct', 0.508924841880798... | 32 | 2 | null | 0.62 | 21 | 4 | 47 | 4 | 11 | 17 | 11 | 21 | 21 | 90 | 1 | 31 |
1,072 | data | https://github.com/bigscience-workshop/biomedical | [] | null | [] | [] | null | null | null | bigscience-workshop/biomedical | biomedical | 399 | 106 | 28 | Python | null | Tools for curating biomedical training data for large-scale language modeling | bigscience-workshop | 2024-01-09 | 2021-09-16 | 123 | 3.225173 | https://avatars.githubusercontent.com/u/82455566?v=4 | Tools for curating biomedical training data for large-scale language modeling | [] | [] | 2023-12-06 | [('qanastek/drbert', 0.6520806550979614, 'llm', 0), ('ai21labs/lm-evaluation', 0.6412531137466431, 'llm', 0), ('togethercomputer/redpajama-data', 0.6301681995391846, 'llm', 0), ('cg123/mergekit', 0.6185329556465149, 'llm', 0), ('freedomintelligence/llmzoo', 0.6107045412063599, 'llm', 0), ('hannibal046/awesome-llm', 0.6... | 56 | 6 | null | 0.71 | 10 | 8 | 28 | 1 | 0 | 0 | 0 | 10 | 1 | 90 | 0.1 | 31 |
1,091 | ml-interpretability | https://github.com/alignmentresearch/tuned-lens | [] | null | [] | [] | null | null | null | alignmentresearch/tuned-lens | tuned-lens | 318 | 32 | 6 | Python | https://tuned-lens.readthedocs.io/en/latest/ | Tools for understanding how transformer predictions are built layer-by-layer | alignmentresearch | 2024-01-11 | 2022-10-03 | 69 | 4.599174 | https://avatars.githubusercontent.com/u/108596820?v=4 | Tools for understanding how transformer predictions are built layer-by-layer | ['machine-learning', 'pytorch', 'transformers'] | ['machine-learning', 'pytorch', 'transformers'] | 2023-09-11 | [('eleutherai/knowledge-neurons', 0.6871256828308105, 'ml-interpretability', 1), ('huggingface/transformers', 0.6621186137199402, 'nlp', 2), ('opengeos/earthformer', 0.6345276832580566, 'gis', 0), ('cdpierse/transformers-interpret', 0.6314489245414734, 'ml-interpretability', 2), ('nvidia/megatron-lm', 0.629341065883636... | 5 | 3 | null | 2.69 | 3 | 1 | 16 | 4 | 5 | 5 | 5 | 3 | 2 | 90 | 0.7 | 31 |
997 | finance | https://github.com/lballabio/quantlib-swig | [] | null | [] | [] | null | null | null | lballabio/quantlib-swig | QuantLib-SWIG | 311 | 273 | 38 | SWIG | null | QuantLib wrappers to other languages | lballabio | 2024-01-11 | 2015-12-17 | 423 | 0.733985 | null | QuantLib wrappers to other languages | ['quantitative-finance'] | ['quantitative-finance'] | 2024-01-12 | [('enthought/pyql', 0.5862199664115906, 'finance', 0), ('goldmansachs/gs-quant', 0.5069200396537781, 'finance', 0), ('ta-lib/ta-lib-python', 0.505255401134491, 'finance', 1)] | 82 | 2 | null | 2.44 | 18 | 16 | 98 | 0 | 5 | 5 | 5 | 18 | 13 | 90 | 0.7 | 31 |
893 | gis | https://github.com/amazon-science/earth-forecasting-transformer | [] | null | [] | [] | null | null | null | amazon-science/earth-forecasting-transformer | earth-forecasting-transformer | 310 | 53 | 12 | Jupyter Notebook | null | Official implementation of Earthformer | amazon-science | 2024-01-10 | 2022-09-12 | 72 | 4.29703 | https://avatars.githubusercontent.com/u/70298811?v=4 | Official implementation of Earthformer | [] | [] | 2023-07-16 | [('opengeos/earthformer', 0.5462614893913269, 'gis', 0)] | 7 | 4 | null | 0.1 | 7 | 2 | 16 | 6 | 0 | 0 | 0 | 7 | 24 | 90 | 3.4 | 31 |
1,400 | finance | https://github.com/chancefocus/pixiu | ['language-model', 'llm'] | null | [] | [] | null | null | null | chancefocus/pixiu | PIXIU | 300 | 26 | 6 | Python | null | This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI). | chancefocus | 2024-01-14 | 2023-06-02 | 34 | 8.677686 | https://avatars.githubusercontent.com/u/26429143?v=4 | This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI). | ['aifinance', 'chatgpt', 'fintech', 'gpt-4', 'large-language-models', 'llama', 'machine-learning', 'named-entity-recognition', 'natural-language-processing', 'nlp', 'pixiu', 'question-answering', 'sentiment-analysis', 'stock-price-prediction', 'text-classification'] | ['aifinance', 'chatgpt', 'fintech', 'gpt-4', 'language-model', 'large-language-models', 'llama', 'llm', 'machine-learning', 'named-entity-recognition', 'natural-language-processing', 'nlp', 'pixiu', 'question-answering', 'sentiment-analysis', 'stock-price-prediction', 'text-classification'] | 2023-12-03 | [('ai4finance-foundation/fingpt', 0.7477177381515503, 'finance', 8), ('ai4finance-foundation/finrl', 0.5721709132194519, 'finance', 1), ('mindsdb/mindsdb', 0.5329363346099854, 'data', 2), ('microsoft/qlib', 0.5296194553375244, 'finance', 2), ('argilla-io/argilla', 0.5267559289932251, 'nlp', 5), ('llmware-ai/llmware', 0... | 7 | 1 | null | 2.69 | 11 | 8 | 8 | 1 | 0 | 0 | 0 | 11 | 3 | 90 | 0.3 | 31 |
651 | template | https://github.com/sqlalchemy/mako | [] | null | [] | [] | null | null | null | sqlalchemy/mako | mako | 293 | 55 | 12 | Python | https://www.makotemplates.org | Mako Templates for Python | sqlalchemy | 2024-01-04 | 2018-11-26 | 270 | 1.084611 | https://avatars.githubusercontent.com/u/6043126?v=4 | Mako Templates for Python | [] | [] | 2023-11-08 | [('pyscaffold/pyscaffold', 0.5707492828369141, 'template', 0), ('martinheinz/python-project-blueprint', 0.5644561648368835, 'template', 0), ('pallets/flask', 0.5588720440864563, 'web', 0), ('eugeneyan/python-collab-template', 0.5552263855934143, 'template', 0), ('klen/muffin', 0.5490294694900513, 'web', 0), ('pallets/j... | 59 | 7 | null | 0.08 | 3 | 2 | 62 | 2 | 1 | 13 | 1 | 3 | 9 | 90 | 3 | 31 |
1,355 | time-series | https://github.com/wilsonrljr/sysidentpy | ['dynamical-systems'] | null | [] | [] | null | null | null | wilsonrljr/sysidentpy | sysidentpy | 282 | 55 | 12 | Python | https://sysidentpy.org | A Python Package For System Identification Using NARMAX Models | wilsonrljr | 2024-01-05 | 2019-03-13 | 254 | 1.106502 | null | A Python Package For System Identification Using NARMAX Models | ['data-science', 'dynamical-systems', 'machine-learning', 'narmax', 'narx', 'system-identification', 'time-series'] | ['data-science', 'dynamical-systems', 'machine-learning', 'narmax', 'narx', 'system-identification', 'time-series'] | 2023-11-22 | [('dynamicslab/pysindy/', 0.6205930113792419, 'math', 3), ('alkaline-ml/pmdarima', 0.5545415878295898, 'time-series', 2), ('artemyk/dynpy', 0.5530008673667908, 'sim', 0), ('unit8co/darts', 0.5214325785636902, 'time-series', 3), ('firmai/atspy', 0.5202825665473938, 'time-series', 1), ('ta-lib/ta-lib-python', 0.512916803... | 12 | 7 | null | 2.19 | 13 | 9 | 59 | 2 | 4 | 3 | 4 | 13 | 12 | 90 | 0.9 | 31 |
856 | ml-ops | https://github.com/astronomer/airflow-chart | [] | null | [] | [] | null | null | null | astronomer/airflow-chart | airflow-chart | 261 | 93 | 47 | Python | null | A Helm chart to install Apache Airflow on Kubernetes | astronomer | 2024-01-13 | 2020-01-22 | 209 | 1.243703 | https://avatars.githubusercontent.com/u/12449437?v=4 | A Helm chart to install Apache Airflow on Kubernetes | ['airflow', 'apache-airflow', 'helm-chart', 'kubernetes'] | ['airflow', 'apache-airflow', 'helm-chart', 'kubernetes'] | 2023-12-14 | [('astronomer/astronomer', 0.8572540283203125, 'ml-ops', 2)] | 49 | 3 | null | 1.42 | 16 | 15 | 48 | 1 | 22 | 28 | 22 | 16 | 9 | 90 | 0.6 | 31 |
1,471 | data | https://github.com/piccolo-orm/piccolo_admin | [] | null | [] | [] | null | null | null | piccolo-orm/piccolo_admin | piccolo_admin | 256 | 32 | 7 | Python | https://piccolo-orm.com/ecosystem/ | A powerful web admin for your database. | piccolo-orm | 2024-01-13 | 2019-06-25 | 240 | 1.066667 | https://avatars.githubusercontent.com/u/45742130?v=4 | A powerful web admin for your database. | ['admin', 'asgi', 'asyncio', 'cms', 'content-management-system', 'dashboard', 'database', 'fastapi', 'piccolo', 'postgresql', 'sqlite', 'starlette', 'vuejs'] | ['admin', 'asgi', 'asyncio', 'cms', 'content-management-system', 'dashboard', 'database', 'fastapi', 'piccolo', 'postgresql', 'sqlite', 'starlette', 'vuejs'] | 2023-11-18 | [('tiangolo/full-stack-fastapi-postgresql', 0.6423637866973877, 'template', 2), ('aminalaee/sqladmin', 0.6254207491874695, 'data', 5), ('fastapi-admin/fastapi-admin', 0.6113201975822449, 'web', 3), ('zenodo/zenodo', 0.5565163493156433, 'util', 1), ('coleifer/peewee', 0.5553250908851624, 'data', 1), ('prefecthq/server',... | 17 | 5 | null | 1.38 | 30 | 26 | 55 | 2 | 24 | 28 | 24 | 30 | 17 | 90 | 0.6 | 31 |
1,549 | llm | https://github.com/rcgai/simplyretrieve | [] | null | [] | [] | null | null | null | rcgai/simplyretrieve | SimplyRetrieve | 175 | 15 | 6 | Python | null | Lightweight chat AI platform featuring custom knowledge, open-source LLMs, prompt-engineering, retrieval analysis. Highly customizable. For Retrieval-Centric & Retrieval-Augmented Generation. | rcgai | 2024-01-12 | 2023-07-24 | 27 | 6.447368 | null | Lightweight chat AI platform featuring custom knowledge, open-source LLMs, prompt-engineering, retrieval analysis. Highly customizable. For Retrieval-Centric & Retrieval-Augmented Generation. | ['artificial-intelligence', 'chat-ai', 'generative-ai', 'huggingface', 'large-language-models', 'machine-learning', 'natural-language-processing', 'nlp', 'prompt-engineering', 'retrieval-augmented-generation', 'retrieval-centric-generation'] | ['artificial-intelligence', 'chat-ai', 'generative-ai', 'huggingface', 'large-language-models', 'machine-learning', 'natural-language-processing', 'nlp', 'prompt-engineering', 'retrieval-augmented-generation', 'retrieval-centric-generation'] | 2023-12-22 | [('embedchain/embedchain', 0.6877291202545166, 'llm', 0), ('deepset-ai/haystack', 0.67171311378479, 'llm', 4), ('larsbaunwall/bricky', 0.6707216501235962, 'llm', 0), ('deeppavlov/deeppavlov', 0.6620361804962158, 'nlp', 3), ('rasahq/rasa', 0.660693347454071, 'llm', 3), ('nomic-ai/gpt4all', 0.6575261950492859, 'llm', 0),... | 2 | 0 | null | 2.38 | 2 | 0 | 6 | 1 | 4 | 8 | 4 | 2 | 6 | 90 | 3 | 31 |
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