{"data":{"slug":"octo-models-octo","name":"octo","tagline":"Transformer-based robot policy trained on a diverse mix of robot trajectories.","github_url":"https://github.com/octo-models/octo","owner":"octo-models","repo":"octo","owner_avatar_url":"https://avatars.githubusercontent.com/u/153724612?v=4","primary_language":"Python","stars":1722,"forks":276,"topics":[],"archived":false,"github_pushed_at":"2024-07-31T00:26:15+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/octo-models-octo","markdown_url":"https://www.graphcanon.com/tools/octo-models-octo.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/octo-models-octo","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=octo-models-octo","description":"Octo is a transformer-based robot policy trained on a diverse mix of 800k robot trajectories.","homepage_url":"https://octo-models.github.io/","license":"MIT","open_issues":96,"watchers":19,"ai_summary":"Octo includes code for training and finetuning transformer-based models aimed at controlling robots, leveraging Jax for GPU and TPU support. The repository emphasizes installation setup for different hardware configurations to facilitate model training.","readme_excerpt":"## Installation\n```bash\nconda create -n octo python=3.10\nconda activate octo\npip install -e .\npip install -r requirements.txt\n```\nFor GPU:\n```bash\npip install --upgrade \"jax[cuda11_pip]==0.4.20\" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html\n```\n\nFor TPU\n```bash\npip install --upgrade \"jax[tpu]==0.4.20\" -f https://storage.googleapis.com/jax-releases/libtpu_releases.html\n```\nSee the [Jax Github page](https://github.com/google/jax) for more details on installing Jax.\n\nTest the installation by finetuning on the debug dataset:\n```bash\npython scripts/finetune.py --config.pretrained_path=hf://rail-berkeley/octo-small-1.5 --debug\n```","github_created_at":"2023-12-13T09:58:56+00:00","created_at":"2026-07-11T23:09:55.456023+00:00","updated_at":"2026-08-02T00:00:09.990253+00:00","categories":[{"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":"gpu","name":"gpu"},{"slug":"jax","name":"jax"},{"slug":"robotics","name":"robotics"},{"slug":"tpu","name":"tpu"},{"slug":"transformer","name":"transformer"}],"trust":{"provenance":{"is_fork":false,"github_id":731075982,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-02T00:00:09.202Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":731,"last_release_at":"2024-05-24T00:28:01Z"},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":48,"high_count":0,"last_scan_at":"2026-07-11T23:10:01.604Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-02T00:00:09.683Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-02T00:00:09.683Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-02T00:00:09.683Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["Need advanced model finetuning with a pre-existing transformer foundation","Working on hardware accelerated applications leveraging GPUs or TPUs"],"when_not_to_use":["If your project requires real-time decision-making without access to GPU/TPU resources","Looking for simpler, more generalized model training tools outside robot control tasks"],"source":"enrich:decision_facts","observed_at":"2026-07-12T12:58:58.060Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Octo focuses on transformer-based models for robot control, emphasizing diverse trajectory training and compatibility with both GPU and TPU via Jax."}]}}