Fine-tuning Llama-3, Mistral and Mixtral with Anyscale
This blog post provides a comprehensive guide on fine-tuning large language models (LLMs) such as Llama-3, Mistral, and Mixtral using Anyscale. It covers the entire process from preparing input data to launching the fine-tuning job and monitoring the process. The article also discusses serving your model with Anyscale's ray-llm library, including how to serve both LoRA and full-parameter fine-tuned models. Additionally, it offers tips on optimizing for compute cost and monitoring the training progress.
Company
Anyscale
Date published
Sept. 11, 2024
Author(s)
Marwan Sarieddine and Kamil Kaczmarek
Word count
2256
Language
English
Hacker News points
None found.