{"data":{"slug":"wandb-wandb","name":"wandb","tagline":"Weights & Biases platform for model training and management","github_url":"https://github.com/wandb/wandb","owner":"wandb","repo":"wandb","owner_avatar_url":"https://avatars.githubusercontent.com/u/26401354?v=4","primary_language":"Python","stars":11262,"forks":899,"topics":["ai","collaboration","data-science","data-versioning","deep-learning","experiment-track","hyperparameter-optimization","hyperparameter-search","hyperparameter-tuning","jax","keras","machine-learning","ml-platform","mlops","model-versioning","pytorch","reinforcement-learning","reproducibility","tensorflow"],"archived":false,"github_pushed_at":"2026-09-27T03:28:37+00:00","maintenance_label":"Very active","stars_delta_30d":49,"url":"https://www.graphcanon.com/tools/wandb-wandb","markdown_url":"https://www.graphcanon.com/tools/wandb-wandb.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/wandb-wandb","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=wandb-wandb","description":"The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.","homepage_url":"https://wandb.ai","license":"MIT","open_issues":993,"watchers":63,"ai_summary":"Provides tools to train and fine-tune models, manage experimentation, hyperparameter tuning, and transition from experiment to production.","readme_excerpt":"## Install the wandb library\n\n```shell\npip install wandb\n```\n\n---\n\n# W&B Hosting Options\n\nWeights & Biases is available in the cloud or installed on your private infrastructure. Set up a W&B Server in a production environment in one of three ways:\n\n1. [Multi-tenant Cloud](https://docs.wandb.ai/platform/hosting/hosting-options/multi_tenant_cloud?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=hosting): Fully managed platform deployed in W&B’s Google Cloud Platform (GCP) account in GCP’s North America regions.\n2. [Dedicated Cloud](https://docs.wandb.ai/platform/hosting/hosting-options/dedicated_cloud?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=hosting): Single-tenant, fully managed platform deployed in W&B’s AWS, GCP, or Azure cloud accounts. Each Dedicated Cloud instance has its own isolated network, compute and storage from other W&B Dedicated Cloud instances.\n3. [Self-Managed](https://docs.wandb.ai/platform/hosting/hosting-options/self-managed?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=hosting): Deploy W&B Server on your AWS, GCP, or Azure cloud account or within your on-premises infrastructure.\n\nSee the [Hosting documentation](https://docs.wandb.ai/platform/hosting?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=hosting) in the W&B Developer Guide for more information.\n\n \n\n---\n\n# License\n\n[MIT License](https://github.com/wandb/wandb/blob/main/LICENSE)","github_created_at":"2017-03-24T05:46:23+00:00","created_at":"2026-07-11T23:26:09.884697+00:00","updated_at":"2026-09-27T06:00:40.905608+00:00","categories":[{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"},{"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":"ai","name":"ai"},{"slug":"collaboration","name":"collaboration"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"hyperparameter-optimization","name":"hyperparameter-optimization"},{"slug":"machine-learning","name":"machine-learning"},{"slug":"mlops","name":"mlops"},{"slug":"model-versioning","name":"model-versioning"},{"slug":"pytorch","name":"pytorch"}],"trust":{"provenance":{"is_fork":false,"github_id":86031674,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-27T06:00:39.919Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":4,"days_since_push":0,"last_release_at":"2026-09-09T00:28:20Z","stars_delta_30d":49,"open_issues_delta_30d":87},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:26:13.344Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-27T06:00:40.553Z"},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-09-27T06:00:40.553Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-09-27T06:00:40.553Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-09-27T06:00:40.553Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["Need extensive collaboration features for teams working on deep-learning projects","Requiring a platform that supports all major ML frameworks like Tensorflow, PyTorch, Jax","Aiming to host the tool in a flexible environment, from public cloud to fully self-managed setups"],"when_not_to_use":["Looking for a lightweight solution without extensive collaboration features","Focusing on simple models where detailed experiment tracking is unnecessary","Operating within environments that strictly forbid third-party hosting solutions"],"source":"enrich:decision_facts","observed_at":"2026-07-17T04:19:41.028Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"wandb excels in streamlined experiment tracking and model versioning across multiple machine learning frameworks."}]}}