Fine-tune GPT-3.5 or Llama 2 with one instruction
Fine-tuning LLMs like Llama 2 and GPT-3.5 can be frustrating and complicated, especially as you need to gather training data.
To address this challenge, HyperWrite CEO Matt Schumer has developed a very useful tool, gpt-llm-trainer, which streamlines the fine-tuning process for LLMs.
You provide gpt-llm-trainer with a description of your task, along with the number of examples and the level of creativity. It takes care of the rest of the process by generating training examples and fine-tuning the model.
Key findings:
gpt-llm-trainer uses “model distillation,” a technique that uses a strong model as a teacher to train a smaller model
The tool generates the examples with GPT-4
Matt has released two Google Colab notebooks, one for training GPT-3.5 and another for Llama 2, which you can run from your browser
Model distillation is not suitable for all tasks, but when the teacher model outperforms your model, you can use it
Models fine-tuned with GPT-4 cannot be used for commercial purposes because of OpenAI’s ToS
Read more about gpt-llm-trainer and how to use it on TechTalks.
For more on LLMs:
How to customize LLMs like ChatGPT with your own data and documents
How to create a private ChatGPT that interacts with your local documents
Recommendations:
My go-to platform for working with ChatGPT, GPT-4, and Claude is ForeFront.ai, which has a super-flexible pricing plan and plenty of good features for writing and coding.