“Return Valid JSON” Is Not Structured Output: What Constrained Decoding Actually Does at the Token…
📰 Medium · Machine Learning
Learn how constrained decoding works in LLMs to generate structured output like valid JSON
Action Steps
- Implement constrained decoding in your LLM to generate valid JSON output
- Use the 'Return only valid JSON' instruction in your composer prompt to test the decoding
- Configure your LLM to handle errors and exceptions when generating JSON output
- Apply constrained decoding to other structured output formats like XML or CSV
- Test and evaluate the performance of your LLM with constrained decoding
Who Needs to Know This
Machine learning engineers and developers working with LLMs can benefit from understanding constrained decoding to improve their model's output
Key Insight
💡 Constrained decoding is a technique used in LLMs to generate structured output by limiting the possible tokens at each step
Share This
🤖 Constrained decoding in LLMs helps generate structured output like valid JSON #LLMs #MachineLearning
Key Takeaways
Learn how constrained decoding works in LLMs to generate structured output like valid JSON
Full Article
In my Conversion Engine, every LLM call ends with some version of the same instruction: “Return only valid JSON.” The composer prompt says… Continue reading on Medium »
DeepCamp AI