bupticybee/FastLoRAChat
Instruct-tune LLaMA on consumer hardware with shareGPT data
This project helps developers and researchers fine-tune large language models (LLMs) like LLaMA for multi-round, multi-language chat on more affordable consumer graphics cards. It takes a base LLaMA model and conversational datasets (like ShareGPT) as input, then outputs a specialized chat model ready for deployment. This is ideal for those who want to customize LLMs without needing expensive, high-end hardware.
125 stars. No commits in the last 6 months.
Use this if you need to adapt a LLaMA model for specific conversational tasks or domains using readily available, lower-cost GPUs.
Not ideal if you're looking for an out-of-the-box solution that doesn't require any technical setup or custom training.
Stars
125
Forks
2
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Apr 20, 2023
Commits (30d)
0
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