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awesome-llama: https://github.com/tatsu-lab/stanford_alpaca

deep-learning instruction-following language-model

Score: 11.933574708403432

Last synced: about 6 hours ago
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Repository metadata:

Code and documentation to train Stanford's Alpaca models, and generate the data.


Owner metadata:


GitHub Events

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Last Year

Committers metadata

Last synced: 4 days ago

Total Commits: 31
Total Committers: 5
Avg Commits per committer: 6.2
Development Distribution Score (DDS): 0.581

Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0

Name Email Commits
Xuechen Li l****n@g****m 13
Rohan Taori r****3@g****m 9
Yann Dubois y****6@g****m 5
Tianyi z****x@g****m 3
Ikko Eltociear Ashimine e****r@g****m 1

Issue and Pull Request metadata

Last synced: about 1 month ago

Total issues: 97
Total pull requests: 25
Average time to close issues: 4 days
Average time to close pull requests: 4 months
Total issue authors: 82
Total pull request authors: 24
Average comments per issue: 4.12
Average comments per pull request: 0.52
Merged pull request: 2
Bot issues: 0
Bot pull requests: 0

Past year issues: 2
Past year pull requests: 1
Past year average time to close issues: 1 day
Past year average time to close pull requests: 7 minutes
Past year issue authors: 2
Past year pull request authors: 1
Past year average comments per issue: 1.0
Past year average comments per pull request: 0.0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0

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Dependencies

requirements.txt pypi
  • fire *
  • numpy *
  • openai *
  • rouge_score *
  • sentencepiece *
  • tokenizers >=0.13.3
  • torch *
  • transformers >=4.28.1
  • wandb *