{"id":29860280,"url":"https://github.com/carlesonielfa/qwen3_span_extraction","last_synced_at":"2026-04-20T04:03:01.147Z","repository":{"id":305095846,"uuid":"1019680362","full_name":"carlesonielfa/qwen3_span_extraction","owner":"carlesonielfa","description":"This is the code repository for the blog post \"Can we assess span-level relevance with dense embedding models?\".","archived":false,"fork":false,"pushed_at":"2025-07-18T06:17:15.000Z","size":1988,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-07-30T03:48:08.086Z","etag":null,"topics":["colbert","embeddings","jina","qwen3","rag","relevance","retrieval","semantic","token"],"latest_commit_sha":null,"homepage":"https://onielfa.com/articles/qwen3_span_extraction","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/carlesonielfa.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-07-14T17:46:21.000Z","updated_at":"2025-07-18T06:17:19.000Z","dependencies_parsed_at":"2025-07-18T10:29:44.506Z","dependency_job_id":"75241468-a74e-4dc3-b83b-c4f1e76c79c1","html_url":"https://github.com/carlesonielfa/qwen3_span_extraction","commit_stats":null,"previous_names":["carlesonielfa/qwen3_span_extraction"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/carlesonielfa/qwen3_span_extraction","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/carlesonielfa%2Fqwen3_span_extraction","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/carlesonielfa%2Fqwen3_span_extraction/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/carlesonielfa%2Fqwen3_span_extraction/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/carlesonielfa%2Fqwen3_span_extraction/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/carlesonielfa","download_url":"https://codeload.github.com/carlesonielfa/qwen3_span_extraction/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/carlesonielfa%2Fqwen3_span_extraction/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32032305,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-20T00:18:06.643Z","status":"online","status_checked_at":"2026-04-20T02:00:06.527Z","response_time":94,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["colbert","embeddings","jina","qwen3","rag","relevance","retrieval","semantic","token"],"created_at":"2025-07-30T03:17:06.051Z","updated_at":"2026-04-20T04:03:01.141Z","avatar_url":"https://github.com/carlesonielfa.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Can we assess span-level relevance with dense embedding models?\n\nThis is the code repository for the blog post [Can we assess span-level relevance with dense embedding models?](https://onielfa.com/articles/qwen3_span_extraction/).\n\nIt contains the jupyter notebook from which the web page was generated, as well as the code for the `manim` animations used in the post.\n\n## How to run the notebook\n\nThe project's requirements are in the `pyproject.toml` file. You can install them using any Python package manager, such as `uv`, `poetry`, or `pdm`.\n\n```bash\nuv sync\n```\nor\n```bash\npoetry install\n```\nor\n```bash\npdm install\n```\n\nIf you wish to use `pip`, a `requirements.txt` file is also available:\n\n```bash\npip install -r requirements.txt\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcarlesonielfa%2Fqwen3_span_extraction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcarlesonielfa%2Fqwen3_span_extraction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcarlesonielfa%2Fqwen3_span_extraction/lists"}