{"data":{"slug":"internlm-lmdeploy","name":"lmdeploy","tagline":"LMDeploy is a toolkit for compressing, deploying, and serving LLMs.","github_url":"https://github.com/InternLM/lmdeploy","owner":"InternLM","repo":"lmdeploy","owner_avatar_url":"https://avatars.githubusercontent.com/u/135356492?v=4","primary_language":"Python","stars":7952,"forks":703,"topics":["codellama","cuda-kernels","deepspeed","fastertransformer","internlm","llama","llama2","llama3","llm","llm-inference","turbomind"],"archived":false,"github_pushed_at":"2026-07-10T11:34:53+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/internlm-lmdeploy","markdown_url":"https://www.graphcanon.com/tools/internlm-lmdeploy.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/internlm-lmdeploy","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=internlm-lmdeploy","description":"LMDeploy is a toolkit for compressing, deploying, and serving LLMs.","homepage_url":"https://lmdeploy.readthedocs.io/en/latest","license":"Apache-2.0","open_issues":597,"watchers":55,"ai_summary":null,"readme_excerpt":"## Installation\n\nIt is recommended installing lmdeploy using pip in a conda environment (python 3.10 - 3.13):\n\n```shell\nconda create -n lmdeploy python=3.12 -y\nconda activate lmdeploy\npip install lmdeploy\n```\n\nStarting from **v0.13.0**, the default prebuilt wheels published on **PyPI** are built against **CUDA 12.8**, so `pip install lmdeploy` is sufficient for typical setups including GeForce RTX 50 series.\n\n---\n\n# License\n\nThis project is released under the [Apache 2.0 license](LICENSE).","github_created_at":"2023-06-15T12:38:06+00:00","created_at":"2026-07-11T10:37:53.448707+00:00","updated_at":"2026-07-12T01:56:00.748351+00:00","categories":[{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"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":"codellama","name":"codellama"},{"slug":"cuda-kernels","name":"cuda-kernels"},{"slug":"deepspeed","name":"deepspeed"},{"slug":"fastertransformer","name":"fastertransformer"},{"slug":"internlm","name":"internlm"},{"slug":"llama","name":"llama"},{"slug":"llama2","name":"llama2"},{"slug":"llama3","name":"llama3"}],"trust":{"provenance":{"is_fork":false,"github_id":654122609,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T10:37:53.977Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":4,"days_since_push":0,"last_release_at":"2026-06-24T04:36:56Z"},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T10:37:54.793Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T10:37:54.457Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-07-11T10:37:54.457Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-11T10:37:54.457Z"}}}}