{"id":20664765,"url":"https://github.com/0x7o/bleurt-deploy","last_synced_at":"2026-04-24T07:33:30.724Z","repository":{"id":159304416,"uuid":"590712935","full_name":"0x7o/bleurt-deploy","owner":"0x7o","description":"Bleurt metric deployment","archived":false,"fork":false,"pushed_at":"2023-02-26T12:24:04.000Z","size":9,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-17T11:22:35.831Z","etag":null,"topics":["bert-model","bleurt","metrics","transformer"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/0x7o.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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}},"created_at":"2023-01-19T02:40:13.000Z","updated_at":"2024-01-02T22:24:02.000Z","dependencies_parsed_at":"2023-06-11T23:38:59.485Z","dependency_job_id":null,"html_url":"https://github.com/0x7o/bleurt-deploy","commit_stats":null,"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"purl":"pkg:github/0x7o/bleurt-deploy","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/0x7o%2Fbleurt-deploy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/0x7o%2Fbleurt-deploy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/0x7o%2Fbleurt-deploy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/0x7o%2Fbleurt-deploy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/0x7o","download_url":"https://codeload.github.com/0x7o/bleurt-deploy/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/0x7o%2Fbleurt-deploy/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32214415,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-24T03:15:14.334Z","status":"ssl_error","status_checked_at":"2026-04-24T03:15:11.608Z","response_time":64,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["bert-model","bleurt","metrics","transformer"],"created_at":"2024-11-16T19:26:06.446Z","updated_at":"2026-04-24T07:33:30.708Z","avatar_url":"https://github.com/0x7o.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Bleurt Model API\n\nThis project is a REST API that allows you to use the pre-trained \"Elron/bleurt-large-512\" model to predict the similarity scores between a set of reference and candidate sentences. The API is built using the FastAPI framework and the Hugging Face Transformers library.\n\n## Requirements\n\n- Python 3.6 or higher\n- PyTorch 1.5 or higher\n- FastAPI\n- Transformers\n\n## Docker\n\nYou can run the API using Docker. You must have Docker installed on your machine to do this.\n\nFirst, build the Docker image:\n\n```bash\ndocker build -t bleurt-api .\n```\n\nThen, run the Docker container:\n\n```bash\ndocker run -d -p 5000:5000 --gpus=all bleurt-api\n```\n\nTest the API by sending a POST request to http://localhost:8000/predict with a JSON payload containing the references and candidates.\n\n## Example\n\n```json\n{\n  \"references\": [\"This is a great product\", \"This is a terrible product\"],\n  \"candidates\": [\"This is a fantastic product\", \"This is a horrible product\"]\n}\n```\n\n```json\n{\n  \"scores\": [0.9656828045845032, 0.04987005889415741]\n}\n```\n\n## Note\n\nMake sure that the GPU is available if you are running the API in a container. If you are running the API on a machine without a GPU, you can remove the line `model.to(\"cuda\")` from the code.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F0x7o%2Fbleurt-deploy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2F0x7o%2Fbleurt-deploy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F0x7o%2Fbleurt-deploy/lists"}