weights-and-biases
Logs and tracks machine learning experiments with Weights & Biases (W&B, wandb): metrics, hyperparameters, checkpoints, sweeps, artifacts with lineage, model registry, custom charts and shareable reports. Includes integrations for PyTorch, HuggingFace Transformers, PyTorch Lightning and Keras/TensorFlow. Use when logging training runs and comparing them across configurations, running automated hyperparameter sweeps, versioning datasets and models as artifacts, registering model versions, or sharing results with a team workspace. Use when setting up wandb.init for offline or unstable-connection training. Not for general data versioning outside ML runs.
- Version
- 1.0.0
- License
- MIT
Pinned to revision df088027ff23, so it is the text this page describes rather than whatever the author pushed since.
Files
- skills/weights-and-biases/SKILL.md
- skills/weights-and-biases/references/artifacts.md
- skills/weights-and-biases/references/hyperparameter-sweeps.md
- skills/weights-and-biases/references/integration-examples.md
- skills/weights-and-biases/references/integrations.md
- skills/weights-and-biases/references/sweeps.md
Every link opens the file at its source, pinned to the revision this page describes.