Single-instruction fine-tuning of Llama-2
Claude-llm-trainer is a Google Colab project that fine-tunes Llama-2-7B with a single description about the downstream task.
Matt Shumer, the CEO of OthersideAI, has released claude-llm-trainer, a Google Colab project that can create a fine-tuned version of Llama-2-7B with a simple description of the target task.
Claude-llm-trainer uses model distillation to generate training examples using Claude 3. It then uses low-rank adaptation (LoRA) to train Llama-2 with the examples.
The project is very easy to use and can be easily customized for other models such as Mistral, Zephyr, Phi, etc.
If your task can be solved with model distillation, claude-llm-trainer can be a great tool to cut the costs and complexity of training your own model.
To learn more about how claude-llm-trainer works, its limitations, and its use cases, read the full article on TechTalks.
You can find the Colab project here.
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Is it better than just putting the prompt in context though?
Cool system regardless