SwanHubX/SwanLab

Health v2 · maintenance only

Adoption not part of the score

4237 stars · 227 forks observed · 2026-09-30

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

SwanLab is an open-source AI training tracking and visualization platform with a Python SDK, CLI, and cloud or self-hosted dashboard. It integrates with 50+ frameworks including PyTorch, Transformers, LLaMA Factory, and Keras to log metrics, logs, and hardware usage during model training.

Use cases

• track machine learning training experiments
• visualize training metrics like loss and accuracy
• compare experiments against a baseline
• self-host an experiment tracking dashboard
• monitor GPU and hardware usage during training
• log LLM fine-tuning runs with LLaMA Factory or verl
• find a TensorBoard alternative with team collaboration

When to choose

• you need experiment tracking for PyTorch, Transformers, or Keras training runs
• you want a modern, self-hostable alternative to TensorBoard or Weights & Biases
• you train models in a team and need shared dashboards and experiment comparison
• you fine-tune LLMs with integrated frameworks like LLaMA Factory, ms-swift, or verl

When to avoid

• you need general-purpose application monitoring or APM rather than ML training tracking
• your project has nothing to do with machine learning
• you only need simple plotting without experiment management

Facets

library · maturity active

logging monitoring data-visualization machine-learning llm-training cli machine-learning deep-learning data-science large-language-models developer-tools python self-hosted cloud mlops experiment-tracking tensorboard-alternative model-training pytorch transformers self-hosted web-server docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="SwanHubX/SwanLab")