Improving language model behavior by training on a curated dataset

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Fine-tuning language models on a curated dataset can improve their behavior with respect to specific values

intermediate Published 10 Jun 2021
Action Steps
  1. Select categories that have a direct impact on human wellbeing
  2. Describe desired behavior in each category
  3. Create a curated dataset of examples that demonstrate the desired behavior
  4. Fine-tune the language model on the curated dataset
Who Needs to Know This

This technique can be useful for AI engineers and researchers working on language models, as well as product managers and developers who want to integrate language models into their applications

Key Insight

💡 Fine-tuning on a small, curated dataset can significantly improve language model behavior without compromising performance

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🤖 Improve language model behavior with fine-tuning on curated datasets! 💡
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