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Gist is 1. Gather training data 2. Format it into JSONL or Hugging Face Dataset format 3. Use Axolotl or Hugging Face peft to fine-tune 4. Export model to G
by firesteelrain 1y ago
Gist is
1. Gather training data
2. Format it into JSONL or Hugging Face Dataset format
3. Use Axolotl or Hugging Face peft to fine-tune
4. Export model to GGUF or HF format
5. Serve via Ollama
https://adithyask.medium.com/axolotl-is-all-you-need-331d5de1b7c0 https://adithyask.medium.com/axolotl-is-all-you-need-331d5de...
https://www.philschmid.de/fine-tune-llms-in-2025 https://www.philschmid.de/fine-tune-llms-in-2025
https://blog.devgenius.io/complete-guide-to-model-fine-tuning-from-hugging-face-to-axolotl-dc5cdaf1ae27 https://blog.devgenius.io/complete-guide-to-model-fine-tunin...
- ofrzeta 1y agoSo, finetuning? Not so easy with ChatGPT I guess, but thanks for the info anyway.
- firesteelrain 1y agoYes, it takes an existing model and fine tunes it. ChatGPT would be basically extensively prompt engineering in a session. Maybe using their API? I have never tried it personally. When I fine tuned a Mistral 7B model it took hundreds of examples in Alpaca style It’s a lot of work. Maybe OpenAI has a more efficient way of doing it because in my case I had to manually adjust each prompt