Individual skill
weights-and-biases
Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platform
backend/cli/skills/ml-training/weights-and-biases/SKILL.md
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- Last checked
- Nov 2, 2026
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- Repository stars (not skill ratings)
- 4,353
- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
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- agent Repository topic
- ai Repository topic
- bun Repository topic
- cli Repository topic
- llm Repository topic
- ml Repository topic
- open-source Repository topic
- research Repository topic
- science Repository topic
- ai-agent Repository topic
- mlops Declared skill tag
- weights-and-biases Declared skill tag
- wandb Declared skill tag
- experiment-tracking Declared skill tag
- hyperparameter-tuning Declared skill tag
- model-registry Declared skill tag
- collaboration Declared skill tag
- real-time-visualization Declared skill tag
- pytorch Declared skill tag
- tensorflow Declared skill tag
- huggingface Declared skill tag
- data Derived category
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Read excerpt
# Weights & Biases: ML Experiment Tracking & MLOps
## When to Use This Skill
Use Weights & Biases (W&B) when you need to:
- **Track ML experiments** with automatic metric logging
- **Visualize training** in real-time dashboards
- **Compare runs** across hyperparameters and configurations
- **Optimize hyperparameters** with automated sweeps
- **Manage model registry** with versioning and lineage
- **Collaborate on ML projects** with team workspaces
- **Track artifacts** (datasets, models, code) with lineage
**Users**: 200,000+ ML practitioners | **GitHub Stars**: 10.5k+ | **Integrations**: 100+