{"data":{"slug":"hiyouga-fastedit","name":"FastEdit","tagline":"Editing large language models within 10 seconds","github_url":"https://github.com/hiyouga/FastEdit","owner":"hiyouga","repo":"FastEdit","owner_avatar_url":"https://avatars.githubusercontent.com/u/16256802?v=4","primary_language":"Python","stars":1370,"forks":103,"topics":["bloom","chatbots","chatgpt","falcon","gpt","large-language-models","llama","llms","pytorch","transformers"],"archived":false,"github_pushed_at":"2023-08-13T03:52:25+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/hiyouga-fastedit","markdown_url":"https://www.graphcanon.com/tools/hiyouga-fastedit.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/hiyouga-fastedit","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=hiyouga-fastedit","description":"🩹Editing large language models within 10 seconds⚡","homepage_url":null,"license":"Apache-2.0","open_issues":21,"watchers":15,"ai_summary":"FastEdit is a Python library designed for efficient editing of large language models, such as LLaMA and others, using PyTorch.","readme_excerpt":"## Requirements\n\n- Python 3.8+ and PyTorch 1.13.1+\n- 🤗Transformers, Datasets and Accelerate\n- sentencepiece and fire\n\n---\n\n### Hardware Requirements\n\n| Model | Size | Mode | GRAM | Speed |\n| ----- | ---- | ---- | ---- | ----- |\n| LLaMA |   7B | FP16 | 24GB | 7s/it |\n| LLaMA |  13B | FP16 | 32GB | 9s/it |\n\n---\n\n### Installation\n\n```bash\ngit clone https://github.com/hiyouga/FastEdit.git\nconda create -n fastedit python=3.10\nconda activate fastedit\ncd FastEdit\npip install -r requirements.txt\n```\n\nAlternatively, you could use `pip install pyfastedit` to install the `fastedit` package.\n\n---\n\n## License\n\nThis repository is licensed under the [Apache-2.0 License](LICENSE).","github_created_at":"2023-07-09T06:21:30+00:00","created_at":"2026-07-11T23:26:56.534955+00:00","updated_at":"2026-08-03T12:01:54.019294+00:00","categories":[{"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":"bloom","name":"bloom"},{"slug":"chatbots","name":"chatbots"},{"slug":"chatgpt","name":"chatgpt"},{"slug":"falcon","name":"falcon"},{"slug":"gpt","name":"gpt"},{"slug":"large-language-models","name":"large language models"},{"slug":"llama","name":"llama"},{"slug":"llms","name":"llms"}],"trust":{"provenance":{"is_fork":false,"github_id":664177247,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-03T12:01:53.271Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":1086,"last_release_at":"2023-07-17T17:14:19Z"},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":73,"high_count":0,"last_scan_at":"2026-07-11T23:26:58.510Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-03T12:01:53.714Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-03T12:01:53.714Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-03T12:01:53.714Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["Requires Python 3.8+ and PyTorch 1.13.1+. Must also install 🤗Transformers, Datasets, Accelerate, sentencepiece, and fire.","Hardware requirements for a specific model can vary; refer to the provided table for minimum RAM sizes for different models."],"min_ram_gb":-1,"requires_docker":false},"constraints":{"min_ram_gb":-1,"requires_docker":false},"when_to_use":["When rapid iterations on language model edits are necessary, such as testing and tuning with tight feedback loops.","If you aim to work specifically within the FP16 precision mode requiring 24GB RAM for a 7B LLaMA model or 32GB RAM for a 13B version.","When you prefer tools licensed under Apache-2.0 and your project already uses PyTorch as its core framework."],"when_not_to_use":["If your workflow requires integration with TensorFlow instead of PyTorch, since FastEdit is built on top of PyTorch.","For hardware configurations that cannot meet the fast editing mode's requirements; for instance, if you have less than 24GB RAM available.","If rapid edits within seconds are not a priority and longer processing times can be tolerated."],"source":"enrich:decision_facts","observed_at":"2026-07-16T18:50:46.038Z"},"constraint_facets":{"min_ram_gb":-1,"requires_docker":false},"decision_summary":[{"label":"Requirements","value":"Min -1 GB RAM; Requires Python 3.8+ and PyTorch 1.13.1+. Must also install 🤗Transformers, Datasets, Accelerate, sentencepiece, and fire.; Hardware requirements for a specific model can vary; refer to the provided table for minimum RAM sizes for different models."},{"label":"Adopt for","value":"FastEdit is a Python library for quick edits to large language models using PyTorch."}]}}