Fine Tune Base Model or Chat Model For Conversations/Instructions? : r/LocalLLaMA
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Hello amazing community... I've been reading a lot lately about that, what i mostly see from YouTube videos/Medium articles, etc... that people tend to use the base model for fine tuning a conversations/instruct based data. Some little use the chat version. Why is that? Isn't it better to fine tune a model that already knows how to make conversations like llama 2 chat/flacon instruct than a model that is only generative like llama 2/falcon. Falcon is also mentioning this in all their instruct models card in huggingface: "This is an instruct model, which may not be ideal for further…
related reading
- Patterns for Building LLM-based Systems & Productseugeneyan.com
- The Llama Hitchiking Guide to Local LLMs – hackerllamaosanseviero.github.io
- Fine-Tuning Llama-2: Tailoring Models to Unique Applicationsanyscale.com
- Fine-tuning LLMs Guide | Unsloth Documentationdocs.unsloth.ai
- GitHub - karpathy/nanochat: The best ChatGPT that $100 can buy.github.com
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- GitHub - rasbt/LLMs-from-scratch: Implement a ChatGPT-like LLM in PyTorch from scratch, step by stepgithub.com
- Tinkerthinkingmachines.ai
- Stanford CRFMcrfm.stanford.edu
- Scaling Instruction-Finetuned Language Modelsarxiv.org