urchade / GLiNER
Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts) @ NAACL 2024
AI Architecture Analysis
This repository is indexed by RepoMind. By analyzing urchade/GLiNER in our AI interface, you can instantly generate complete architecture diagrams, visualize control flows, and perform automated security audits across the entire codebase.
Our Agentic Context Augmented Generation (Agentic CAG) engine loads full source files into context on-demand, avoiding the fragmentation of traditional RAG systems. Ask questions about the architecture, dependencies, or specific features to see it in action.
Embed this Badge
Showcase RepoMind's analysis directly in your repository's README.
Repository Overview (README excerpt)
Crawler view> [!IMPORTANT] > **š GLiNER2 is Now Available from Fastino Labs!** A unified multi-task model for NER, Text Classification & Structured Data Extraction. Check out fastino-ai/GLiNER2 ā š GLiNER: Generalist and Lightweight Model for Named Entity Recognition --- GLiNER is a framework for training and deploying small Named Entity Recognition (NER) models with zero-shot capabilities. In addition to tradition NER, it also supports joint entity and relation extraction. GLiNER is fine-tunable, optimized to run on CPUs and consumer hardware, and has performance competitive with LLMs several times its size, like ChatGPT and UniNER. Example Notebooks Explore various examples including finetuning, ONNX conversion, and synthetic data generation. ā¢ Example Notebooks ā¢ Finetune on Colab š Installation & Usage Installation Usage After the installation of the GLiNER library, import the class. Following this, you can load your chosen model with and utilize to discern entities within your text. Expected Output šØāš» Model Authors GLiNER was originally developed by: ā¢ Urchade Zaratiana ā¢ Nadi Tomeh ā¢ Pierre Holat ā¢ Thierry Charnois š Maintainers Urchade Zaratiana Member of technical staff at Fastino Ihor Stepanov Co-Founder at Knowledgator š Citations If you find GLiNER useful in your research, please consider citing our papers: Support and funding This project has been supported and funded by **F.initiatives** and **Laboratoire Informatique de Paris Nord**. F.initiatives has been an expert in public funding strategies for R&D, Innovation, and Investments (R&D&I) for over 20 years. With a team of more than 200 qualified consultants, F.initiatives guides its clients at every stage of developing their public funding strategy: from structuring their projects to submitting their aid application, while ensuring the translation of their industrial and technological challenges to public funders. Through its continuous commitment to excellence and integrity, F.initiatives relies on the synergy between methods and tools to offer tailored, high-quality, and secure support. We also extend our heartfelt gratitude to the open-source community for their invaluable contributions, which have been instrumental in the success of this project.