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releasing-research-code
Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)
https://github.com/paperswithcode/releasing-research-code
Last synced: 2 days ago
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🎉 Additional awesome resources for releasing research code
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Hosting pretrained models files
- Google Drive - versioning, 15GB, free bandwidth
- huggingface_hub - versioning, no size limitations, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- AWS S3 - versioning, paid only, paid bandwidth
- DAGsHub - versioning, no size limitations, free bandwith
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
- Google Drive - versioning, 15GB, free bandwidth
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Results leaderboards
- Collective Knowledge - with 40+ leaderboards
- Collective Knowledge - with 40+ leaderboards
- Weights & Biases - Benchmarks - with 9+ leaderboards
- Papers with Code leaderboards - with 4000+ leaderboards
- CodaLab Competitions - with 450+ leaderboards
- EvalAI - with 100+ leaderboards
- NLP Progress - with 90+ leaderboards
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Making project pages
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Making demos, tutorials, executable papers
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Managing model files
- RClone - provides unified access to many different cloud storage providers
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Standardized model interfaces
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✓ ML Code Completeness Checklist
- blog post - neurips2019.csv) and [notebook](notebooks/code_checklist-analysis.pdf) to reproduce this analysis from the post.
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deep-learning
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machine-learning
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python
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model-hub
1
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natural-language-processing
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pretrained-models
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pytorch
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actions
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fastai
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jekyll
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streamlit
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