# haidog-yaqub/MeanFlow

PyTorch implementation of MeanFlow & iMF (one-step generative modeling).

Repository: https://github.com/haidog-yaqub/MeanFlow
Canonical: https://ross.abutalabs.com/products/meanflow
Language: Python
License: MIT
License Family: permissive
Topics: diffusion-models, flow-matching, generative-model
Last push: 2026-07-01T03:26:59+00:00

## Health v2 (maintenance only)
Score: 59/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 90, release rhythm 35, longevity 33
- inputs: {"age_days": 470, "days_push": 63, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1196, forks 70 (observed 2026-08-28T04:03:56.960229+00:00)

## What it is
An unofficial PyTorch implementation of MeanFlow and iMF, one-step generative modeling methods based on flow matching. It provides config-driven training scripts for MNIST, CIFAR-10, and ImageNet latent generation with multi-GPU support via Accelerate.

## Use cases
- train a one-step generative image model
- reproduce MeanFlow paper results in PyTorch
- generate MNIST or CIFAR-10 images with a single sampling step
- experiment with flow matching and CFG distillation
- train latent ImageNet generation models on multiple GPUs

## When to choose
- you want a PyTorch (rather than JAX) implementation of MeanFlow or iMF
- you need one-step generative modeling with classifier-free guidance
- you want ready-made configs for MNIST, CIFAR-10, or ImageNet latent training

## When to avoid
- you need the official, fully supported implementation
- you require Triton JVP kernels or Flash Attention within JVP, which are not yet supported
- you need a production inference library rather than research training code

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, image-processing
- domain: deep-learning, machine-learning, image-processing
- platform: python
- tags: diffusion-models, flow-matching, generative-modeling, pytorch, one-step-generation, research-code, gpu

## Member repositories
- haidog-yaqub/MeanFlow (main) score 59

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:56.960229+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:22:02.485470+00:00, confidence not recorded.
  - readme: https://github.com/haidog-yaqub/MeanFlow (fetched 2026-08-28T04:03:56.960229+00:00, sha 6268238f682f)
- Data as of 2026-08-30T08:39:29.467469+00:00.