Picking a Dataset to Train Your Own GPT Model
- Generative AI
This lesson walks through the solution to an earlier assignment, offering guidance on picking a Hugging Face conversation dataset rather than starting with a closed model like OpenAI's GPT. It walks through browsing Hugging Face's datasets tab, filtering for conversational examples such as mental health counseling chats or function calling data, and checking whether a dataset's license allows the intended use. The lesson recommends downloading a chosen dataset, trimming it down to a curated sample of around ten thousand examples, and reusing the training steps from earlier videos to train a first model.
Key takeaways
- Why starting from a Hugging Face conversation dataset was recommended over using a closed model
- How filtering Hugging Face's datasets tab for conversational examples surfaces options like counseling chats
- Why trimming a dataset of a million conversations down to about ten thousand examples keeps training practical
- What licensing details are worth checking before reusing a public dataset for a training assignment
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