What is Weights & Biases?
Weights & Biases is the go-to AI developer platform for building, managing, and tracking AI models and applications. Whether you're training models, fine-tuning LLMs, or debugging AI applications, W&B has got you covered. It’s trusted by leading AI teams worldwide and integrates seamlessly with popular frameworks like PyTorch, TensorFlow, and LangChain.
What are the features of Weights & Biases?
- Weave: Develop and debug AI applications with ease.
- Traces: Explore and debug AI applications in real-time.
- Evaluations: Rigorous testing for AI applications.
- Guardrails: Block harmful outputs and prompt attacks.
- Models: Track and visualize ML experiments.
- Sweeps: Optimize hyperparameters efficiently.
- Tables: Visualize and explore ML data.
- Registry: Publish and share ML models and datasets.
- Artifacts: Version and manage ML pipelines.
- Reports: Visualize and explore ML data.
- SDK: Log ML experiments and artifacts at scale.
- Automations: Trigger workflows automatically.
What are the use cases of Weights & Biases?
- Develop with LLMs: Train and fine-tune large language models.
- Computer Vision: Build and manage vision models.
- Time Series: Analyze and predict time-based data.
- Recommender Systems: Create personalized recommendation engines.
- Classification & Regression: Solve complex classification and regression problems.
How to use Weights & Biases?
- Weave: Initialize Weave with your project name and start tracking LLM calls.
- Models: Use
wandb.initto start a new run, log metrics, and save model artifacts. - Sweeps: Optimize hyperparameters by configuring sweeps in your project.
- Tables: Visualize your ML data by logging it to W&B tables.
- Automations: Set up triggers to automate workflows in your ML pipeline.
