https://github.com/AGI-Edgerunners/LLM-Adapters

Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"
https://github.com/AGI-Edgerunners/LLM-Adapters

adapters fine-tuning large-language-models parameter-efficient

Last synced: about 1 month ago
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Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"

• Host: GitHub
• URL: https://github.com/AGI-Edgerunners/LLM-Adapters
• Owner: AGI-Edgerunners
• License: apache-2.0
• Created: 2023-03-29T13:34:08.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-03-10T08:20:15.000Z (4 months ago)
• Last Synced: 2024-03-10T09:29:08.573Z (4 months ago)
• Topics: adapters, fine-tuning, large-language-models, parameter-efficient
• Language: Python
• Homepage: https://arxiv.org/abs/2304.01933
• Size: 73.2 MB
• Stars: 900
• Watchers: 11
• Forks: 74
• Open Issues: 36
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• awesome-LLMs-finetuning - LLM-Adapters - Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models". (769 stars) (4. Fine-Tuning / Frameworks)
• awesome-llms-fine-tuning - LLM-Adapters - Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models". (769 stars) (GitHub projects)