Llm Finetuning
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Stable Diffusion Webui Colab | 14,090 | 6 months ago | 16 | unlicense | Jupyter Notebook | |||||
| stable diffusion webui colab | ||||||||||
| Peft | 12,271 |  | 101 | 3 months ago | 11 | December 06, 2023 | 65 | apache-2.0 | Python | |
| 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. | ||||||||||
| Lora | 7,814 |  | 16 | 4 months ago | 3 | August 27, 2023 | 79 | mit | Python | |
| Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models" | ||||||||||
| Chatglm Efficient Tuning | 3,130 | 6 months ago | 6 | August 12, 2023 | apache-2.0 | Python | ||||
| Fine-tuning ChatGLM-6B with PEFT | 基于 PEFT 的高效 ChatGLM 微调 | ||||||||||
| Adapters | 2,354 |  | 7 | a month ago | 18 | April 06, 2023 | 51 | apache-2.0 | Jupyter Notebook | |
| A Unified Library for Parameter-Efficient and Modular Transfer Learning | ||||||||||
| Alpaca Cot | 2,235 | 4 months ago | 30 | apache-2.0 | Jupyter Notebook | |||||
| We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts to initiate any meaningful PR on this repo and integrate as many LLM related technologies as possible. 我们打造了方便研究人员上手和使用大模型等微调平台，我们欢迎开源爱好者发起任何有意义的pr！ | ||||||||||
| Chatglm_finetuning | 1,486 | 6 months ago | 38 | Python | ||||||
| chatglm 6b finetuning and alpaca finetuning | ||||||||||
| Onediff | 787 | 3 months ago | 27 | Python | ||||||
| OneDiff: An out-of-the-box acceleration library for diffusion models. | ||||||||||
| Lorax | 719 | 3 months ago | 45 | apache-2.0 | Python | |||||
| Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs | ||||||||||
| Llm Finetuning | 582 | 5 months ago | 1 | Jupyter Notebook | ||||||
| LLM Finetuning with peft | ||||||||||
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