{"id":18395831,"url":"https://github.com/deepset-ai/nvidia-triton-inference","last_synced_at":"2026-01-21T13:33:27.350Z","repository":{"id":256764306,"uuid":"856346864","full_name":"deepset-ai/nvidia-triton-inference","owner":"deepset-ai","description":"This repository contains setup examples for hosting model inference using NVIDIA triton","archived":false,"fork":false,"pushed_at":"2024-10-01T12:47:51.000Z","size":32,"stargazers_count":0,"open_issues_count":1,"forks_count":2,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-10-23T14:19:46.008Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"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/deepset-ai.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":"2024-09-12T12:31:31.000Z","updated_at":"2024-09-24T16:34:05.000Z","dependencies_parsed_at":"2024-09-13T00:22:32.198Z","dependency_job_id":"c62dcee8-9965-4494-870a-b7b95458c5c5","html_url":"https://github.com/deepset-ai/nvidia-triton-inference","commit_stats":null,"previous_names":["deepset-ai/nvidia-triton-inference"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/deepset-ai/nvidia-triton-inference","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepset-ai%2Fnvidia-triton-inference","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepset-ai%2Fnvidia-triton-inference/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepset-ai%2Fnvidia-triton-inference/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepset-ai%2Fnvidia-triton-inference/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/deepset-ai","download_url":"https://codeload.github.com/deepset-ai/nvidia-triton-inference/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepset-ai%2Fnvidia-triton-inference/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28633763,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-21T04:47:28.174Z","status":"ssl_error","status_checked_at":"2026-01-21T04:47:22.943Z","response_time":86,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 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":[],"created_at":"2024-11-06T02:12:01.936Z","updated_at":"2026-01-21T13:33:27.334Z","avatar_url":"https://github.com/deepset-ai.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# nvidia-triton-inference\nThis repository contains setup examples for hosting model inference using NVIDIA triton\n\n## How to build a triton embedding image\n\n1. Setup your model and tokenizer files\n\n    - move model.onnx to `hf-embedding-template/onnx_model/1/`\n    - move any other model files (model and tokenizer config) to `hf-embedding-template/preprocessing/1/`\n\n2. Start Triton Server and attach shell\n\n    ```\n    docker run --shm-size=16g --gpus all -it --rm -p 8000:8000 -p 8001:8001 -p 8002:8002 -v /hf-embedding-template:/models nvcr.io/nvidia/tritonserver:24.08-py3 bash\n    ```\n\n\n3. Run inside the Triton Container\n\n    ```\n    pip install transformers\n\n    tritonserver --model-repository=/models\n    ```\n\n4. Run client \n\n    ```\n    pip install tritonclient[http]\n\n    python client.py\n    ```\n\n## helm charts\n\nThis repo comes with ready to run helm charts. They can be found under `/helm`. E.g. `text-embedder-trion` is readily configured to run a triton embedding server.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeepset-ai%2Fnvidia-triton-inference","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdeepset-ai%2Fnvidia-triton-inference","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeepset-ai%2Fnvidia-triton-inference/lists"}