thuml/Transfer-Learning-Library

Health v2 · maintenance only

Adoption not part of the score

3931 stars · 602 forks observed · 2026-08-28

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

TLlib is a PyTorch-based open-source library for transfer learning, covering domain adaptation, task adaptation (finetuning), and domain generalization. It provides modular APIs for alignment, translation, self-training, reweighting, and model selection methods, with example code for classification, detection, segmentation, and more.

Use cases

• adapt a model trained on one domain to a new unlabeled domain
• finetune pretrained models for a new task
• improve out-of-distribution generalization of my model
• run semi-supervised learning experiments
• implement DANN or adversarial domain adaptation
• select the best pretrained model for transfer
• do domain adaptation for object detection or segmentation

When to choose

• you need research-grade implementations of domain adaptation and generalization algorithms in PyTorch
• you want a torchvision-consistent API to build new transfer learning methods
• you need examples across many tasks like classification, detection, and keypoint detection

When to avoid

• you need a production serving or AutoML platform rather than an algorithm library
• you work outside PyTorch or outside vision-centric tasks
• you need turnkey no-code transfer learning

Facets

library · maturity active

machine-learning deep-learning image-processing computer-vision machine-learning deep-learning computer-vision artificial-intelligence python cross-platform transfer-learning domain-adaptation domain-generalization pytorch finetuning self-training semi-supervised-learning research gpu

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markdown · JSON · MCP: product_card(name="thuml/Transfer-Learning-Library")