How to fine-tune a large language model with Batch

[kweinmeister]

Hi everyone,

I recently wrote an article about streamlining LLM fine-tuning with Batch, and wanted share the approach here. I demonstrate how to simplify the process using Axolotl, an open-source tool for easier configuration. The key takeaways are:

• Batch handles the heavy lifting of infrastructure. This includes easy GPU access and integration with other GCP services.

• Axolotl simplifies the fine-tuning configuration. With YAML files, you can configure your jobs to use the latest fine-tuning methods like LoRA with many popular models.

• Step-by-step walkthrough included. Learn how to apply the process using Gemma 2 and the databricks-dolly-15k dataset.

Enjoy! Link here:
https://medium.com/google-cloud/model-fine-tuning-made-easy-with-axolotl-on-google-cloud-batch-e67d7...