LLaMA-LoRA-Tuner
FastChat
| LLaMA-LoRA-Tuner | FastChat | |
|---|---|---|
| 6 | 83 | |
| 426 | 34,708 | |
| - | 4.8% | |
| 7.9 | 9.6 | |
| 12 months ago | 5 days ago | |
| Python | Python | |
| - | Apache License 2.0 |
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LLaMA-LoRA-Tuner
- [P] Uptraining a pretrained model using company data?
- (HELP) Token Issue on Generation
- Help with Random Characters and Words on Output
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Fine-tuning LLaMA for research without Meta license
I would like to fine-tune LLaMA using this tuner for a research paper, but I am wondering if it is legal to do so. If it isn't, does anyone have suggestions for alternatives which are similarly user-friendly as the one above, since I am not a good programmer? Any advice would be greatly appreciated, thank you!
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Why run LLMs locally?
The bad news is that, as far as I know, it does require a GPU. The good news is that I've gotten training done with a 7b model on both google colab and kaggle with free accounts. Both have 'just' enough vram to make it work as long as you use load the model in 8bit. Like --load-in-8bit on the command line with oobabooga. The Lora Tuner frontend even has a colab notebook set up to simplify things even more. Though the frontend keeps the LoRA Rank and LoRA Alpha values capped pretty low. Thankfully that's just set in the GUI though. I think it was one of the files in its UI directory. Pretty easy to just hand edit it to allow for higher values if desired.
- How can I train my custom dataset on top of Vicuna?
FastChat
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GPT4.5 or GPT5 being tested on LMSYS?
gpt2-chatbot isn't the only "mystery model" on LMSYS. Another is "deluxe-chat".
When asked about it in October last year, LMSYS replied [0] "It is an experiment we are running currently. More details will be revealed later"
One distinguishing feature of "deluxe-chat": although it gives high quality answers, it is very slow, so slow that the arena displays a warning whenever it is invoked
[0] https://github.com/lm-sys/FastChat/issues/2527
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LLMs on your local Computer (Part 1)
FastChat
- FLaNK AI for 11 March 2024
- FLaNK 04 March 2024
- ChatGPT for Teams
- FastChat: An open platform for training and serving large language models
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LM Studio – Discover, download, and run local LLMs
How does it compare with something like FastChat? https://github.com/lm-sys/FastChat
Feature set seems like a decent amount of overlap. One limitation of FastChat, as far as I can tell, is that one is limited to the models that FastChat supports (though I think it would be minor to modify it to support arbitrary models?)
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Video-LLaVA
Looks like the Vicuna repo is Apache 2.0 also[1].
What's the interpretation of copyright law that would prevent the code being Apache 2.0 based on the source of the fine-tuning dataset?
[1] https://github.com/lm-sys/FastChat
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
Check how to start with FastChat. Support FastChat on GitHub ⭐
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Show HN: ChatAPI – PWA to Use ChatGPT by API Build with Alpine.js
For something a little heavier but much more robust in terms of features/functionality I've been enjoying FastChat: https://github.com/lm-sys/FastChat
It allows you to plug in different backends so that you can use OpenAI compatible clients with various LLM's, selfhosted or otherwise.
What are some alternatives?
CodeCapybara - Open-source Self-Instruction Tuning Code LLM
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
AlpacaDataCleaned - Alpaca dataset from Stanford, cleaned and curated
llama.cpp - LLM inference in C/C++
CodeCapypara - [Moved to: https://github.com/FSoft-AI4Code/CodeCapybara]
gpt4all - gpt4all: run open-source LLMs anywhere
BELLE - BELLE: Be Everyone's Large Language model Engine（开源中文对话大模型）
bitsandbytes - Accessible large language models via k-bit quantization for PyTorch.
lora - Train Large Language Models (LLM) using LoRA
LocalAI - :robot: The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. It allows to generate Text, Audio, Video, Images. Also with voice cloning capabilities.
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
llama-cpp-python - Python bindings for llama.cpp