A Reddit user is seeking advice on a document extraction process that uses a distilled LLM approach. They have trained two 287M encoder models, one for entity recognition (GLiNER) and another for classification, to process court decisions. The user detailed their two-step process: first, using a powerful LLM like Claude Sonnet to label a subset of documents and extract entities, actions, and values, and second, fine-tuning smaller models on this labeled data. They are encountering issues matching the performance of the original LLM and are asking for feedback on their methodology. AI
RANK_REASON User is asking for advice on a technical process, not announcing a new product or research.
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
