{"data":{"slug":"urchade-gliner","name":"GLiNER","tagline":"Generalist and Lightweight Model for Named Entity Recognition","github_url":"https://github.com/urchade/GLiNER","owner":"urchade","repo":"GLiNER","owner_avatar_url":"https://avatars.githubusercontent.com/u/38214774?v=4","primary_language":"Python","stars":3545,"forks":299,"topics":["information-extraction","large-language-models","named-entity-recognition","natural-language-processing","prompt-tuning"],"archived":false,"github_pushed_at":"2026-08-10T09:21:43+00:00","maintenance_label":"Active","stars_delta_30d":143,"url":"https://www.graphcanon.com/tools/urchade-gliner","markdown_url":"https://www.graphcanon.com/tools/urchade-gliner.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/urchade-gliner","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=urchade-gliner","description":"Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts)","homepage_url":"https://urchade.github.io/GLiNER","license":"Apache-2.0","open_issues":96,"watchers":20,"ai_summary":"GLiNER is a Python library designed for extracting various entity types from texts using lightweight named entity recognition techniques.","readme_excerpt":"### Installation\n\n**With pip:**\n```bash\npip install gliner\n```\n\n**With uv (faster):**\n```bash\nuv pip install gliner\n```\n\n**With serving support (Ray Serve):**\n```bash\nuv pip install gliner[serve]  # or: pip install gliner ray[serve]\n```","github_created_at":"2023-11-14T18:11:11+00:00","created_at":"2026-07-07T17:35:47.957095+00:00","updated_at":"2026-08-18T00:01:57.324481+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"information-extraction","name":"information-extraction"},{"slug":"large-language-models","name":"large language models"},{"slug":"named-entity-recognition","name":"named-entity-recognition"},{"slug":"natural-language-processing","name":"natural-language-processing"},{"slug":"prompt-tuning","name":"prompt-tuning"}],"trust":{"provenance":{"is_fork":false,"github_id":718748920,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-18T00:01:56.616Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":1,"days_since_push":7,"last_release_at":"2026-07-24T14:22:26Z","stars_delta_30d":143,"open_issues_delta_30d":-1},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":30,"high_count":0,"last_scan_at":"2026-07-11T11:06:13.137Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-18T00:01:57.055Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-18T00:01:57.055Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-18T00:01:57.055Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When you need a lightweight solution for named entity recognition across various languages","For projects where resource efficiency and fast setup are critical"],"when_not_to_use":["If high precision in niche specializations like medical terms or rare proper nouns is required","In scenarios demanding heavy customization beyond basic named entity recognition capabilities"],"source":"enrich:decision_facts","observed_at":"2026-07-14T18:30:37.893Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"GLiNER is ideal for extracting named entities from text with minimal computational resources."}]}}