AI Model / Text Extraction / RAG
A 150M ModernBERT-based token classification model that extracts verbatim evidence spans for RAG and related pipelines, reducing the need for an LLM call to highlight answers.
The page clearly describes an AI-powered model, its purpose, how it works, and how to use it with Transformers or inside VerbatimRAG. The snapshot includes concrete architecture details, training data domains, example code, and performance context, making it useful for a public directory listing.
The snapshot does not show the full performance table, benchmark numbers, or maintenance/release history, so a visitor cannot judge real-world quality or project activity from this page alone.
Last evaluated just now. Current rank #53. Down 3 spots in the rankings.
JetBrains introduces Mellum2, an open-source 12B model built for software engineering workflows, routing, Q&A, RAG, sub-agents, and private deployment.
An open-source 26M parameter function-calling model designed to run on very small devices, with a local quickstart, Python usage, and a playground for testing and finetuning.
