RL-VIG/LibFewShot

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1069 stars · 200 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LibFewShot is a comprehensive PyTorch library for few-shot learning, implementing many fine-tuning, meta-learning, and metric-learning methods from top venues. It provides a unified framework for training, evaluating, and reproducing few-shot image classification research.

Use cases

• reproduce few-shot learning paper results
• train a prototypical network baseline
• compare meta-learning methods like MAML and R2D2
• benchmark metric-learning few-shot classifiers
• develop a new few-shot learning method on a unified codebase
• fine-tune models for low-shot image classification

When to choose

• you need a unified, well-documented framework for few-shot image classification research
• you want to reproduce or compare many published few-shot methods in one codebase
• you are building new few-shot algorithms on PyTorch

When to avoid

• your task is not image classification (e.g., few-shot NLP or detection)
• you need production deployment rather than research experimentation
• you do not work in PyTorch

Facets

library · maturity active

machine-learning deep-learning machine-learning computer-vision image-processing artificial-intelligence python cross-platform few-shot-learning meta-learning metric-learning fine-tuning pytorch image-classification research-library gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="RL-VIG/LibFewShot")