open-mmlab/mmrazor

Health v2 · maintenance only

Adoption not part of the score

1682 stars · 245 forks observed · 2026-08-28

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

MMRazor is OpenMMLab's model compression toolbox and benchmark built on PyTorch. It provides implementations of neural architecture search, pruning, knowledge distillation, and quantization algorithms for vision tasks like detection, segmentation, and classification.

Use cases

• compress a pytorch detection model with knowledge distillation
• prune a classification network to reduce inference cost
• run neural architecture search with darts or autoslim
• quantize a segmentation model for deployment
• benchmark model compression algorithms on vision tasks

When to choose

• you use the OpenMMLab ecosystem (mmdetection, mmclassification) and want to compress those models
• you need a unified framework for NAS, pruning, and distillation experiments
• you want reproducible benchmarks of compression algorithms on vision models

When to avoid

• you need compression for NLP or transformer LLMs rather than vision models
• you want a lightweight single-technique tool rather than a full framework
• you need actively developed features, as the project's latest release is mid-2024

Facets

library · maturity maintenance

machine-learning deep-learning benchmarking deep-learning computer-vision machine-learning python model-compression knowledge-distillation pruning nas quantization pytorch openmmlab gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="open-mmlab/mmrazor")