{"data":{"slug":"lyogavin-airllm","name":"airllm","tagline":"Inference for AirLLM 70B model with single 4GB GPU","github_url":"https://github.com/lyogavin/airllm","owner":"lyogavin","repo":"airllm","owner_avatar_url":"https://avatars.githubusercontent.com/u/1113905?v=4","primary_language":"Jupyter Notebook","stars":34504,"forks":3626,"topics":["chinese-llm","chinese-nlp","finetune","generative-ai","instruct-gpt","instruction-set","llama","llm","lora","open-models","open-source","open-source-models","qlora"],"archived":false,"github_pushed_at":"2026-09-18T06:25:07+00:00","maintenance_label":"Very active","stars_delta_30d":10321,"url":"https://www.graphcanon.com/tools/lyogavin-airllm","markdown_url":"https://www.graphcanon.com/tools/lyogavin-airllm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/lyogavin-airllm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=lyogavin-airllm","description":"AirLLM 70B inference with single 4GB GPU","homepage_url":null,"license":"Apache-2.0","open_issues":155,"watchers":287,"ai_summary":"AirLLM is a repository that facilitates the inference of a 70B parameter model using a single 4GB GPU, focusing on Chinese language models and generative AI.","readme_excerpt":"### 1. Install package\n\nFirst, install the airllm pip package.\n\n```bash\npip install airllm\n```","github_created_at":"2023-06-12T16:28:41+00:00","created_at":"2026-07-07T17:33:04.588292+00:00","updated_at":"2026-09-20T04:32:43.987768+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"}],"tags":[{"slug":"chinese-llm","name":"chinese-llm"},{"slug":"chinese-nlp","name":"chinese-nlp"},{"slug":"finetune","name":"finetune"},{"slug":"generative-ai","name":"generative-ai"},{"slug":"instruct-gpt","name":"instruct-gpt"},{"slug":"instruction-set","name":"instruction-set"},{"slug":"llama","name":"llama"},{"slug":"llm","name":"llm"}],"trust":{"provenance":{"is_fork":false,"github_id":652712035,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-18T08:41:57.185Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":6,"days_since_push":0,"last_release_at":"2026-09-05T15:43:11Z","stars_delta_30d":10321,"open_issues_delta_30d":40},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":4,"high_count":0,"last_scan_at":"2026-09-18T08:41:59.625Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-18T08:41:55.941Z"},"languages":{"value":["jupyter notebook"],"source":"github.language","observed_at":"2026-09-18T08:41:55.941Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-09-18T08:41:55.941Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["Installation is straightforward via pip."],"min_ram_gb":4,"requires_docker":false},"constraints":{"min_ram_gb":4,"requires_docker":false},"when_to_use":["When you need to perform inference on a 70B parameter model with limited GPU resources, such as a single 4GB GPU.","If your project involves Chinese language models and you require a lightweight solution for generative AI tasks."],"when_not_to_use":["If your project requires inference on models larger than 70B parameters or if you have access to more powerful GPUs than a 4GB model.","For projects that do not involve Chinese language models or generative AI tasks, as AirLLM is specifically optimized for these areas."],"source":"enrich:decision_facts","observed_at":"2026-09-18T12:07:30.570Z"},"constraint_facets":{"min_ram_gb":4,"requires_docker":false},"decision_summary":[{"label":"Requirements","value":"Min 4 GB RAM; Installation is straightforward via pip."},{"label":"Adopt for","value":"AirLLM is a repository that enables the inference of a 70B parameter model using a single 4GB GPU, with a focus on Chinese language models and generative AI."},{"label":"License detail","value":"Apache-2.0"}]}}