# lucidrains/make-a-video-pytorch

Implementation of Make-A-Video, new SOTA text to video generator from Meta AI, in Pytorch

Repository: https://github.com/lucidrains/make-a-video-pytorch
Canonical: https://ross.abutalabs.com/products/make-a-video-pytorch
Language: Python
License: MIT
License Family: permissive
Topics: artificial-intelligence, attention-mechanisms, deep-learning, text-to-video, axial-convolutions
Last push: 2024-05-03T17:34:14+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1434, "days_push": 852, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1986, forks 185 (observed 2026-08-28T04:06:02.719277+00:00)

## What it is
A PyTorch library implementing Make-A-Video, Meta AI's text-to-video generation approach, built around pseudo-3d (axial) convolutions and spatiotemporal attention modules. It provides reusable building blocks (PseudoConv3d, SpatioTemporalAttention) that work on both video and image tensors so models can be pretrained on images and ported to video.

## Use cases
- generate videos from text prompts
- implement text-to-video diffusion models in pytorch
- add temporal attention to a 2d unet
- pretrain on images then fine-tune for video generation
- use pseudo-3d convolutions for spatiotemporal modeling
- research frame interpolation for video synthesis

## When to choose
- you need the Make-A-Video architecture components in PyTorch
- you want to extend a text-to-image model to video generation
- you are doing research on spatiotemporal attention and axial convolutions

## When to avoid
- you need a ready-to-use, fully trained text-to-video model
- you want a production video generation pipeline with inference tooling
- you need a maintained, stable implementation - the repo is marked work-in-progress

## Facets
- artifact type: library
- maturity: experimental
- function: deep-learning, machine-learning, image-processing, video-processing
- domain: deep-learning, machine-learning, artificial-intelligence
- platform: python
- tags: text-to-video, diffusion, pytorch, pseudo-3d-convolutions, spatiotemporal-attention, research-implementation, generative-ai, video

## Member repositories
- lucidrains/make-a-video-pytorch (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:02.719277+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 2026-08-30T03:03:06.695124+00:00, confidence not recorded.
  - readme: https://github.com/lucidrains/make-a-video-pytorch (fetched 2026-08-28T04:06:02.719277+00:00, sha b25a59e4b682)
  - registry_pypi: https://pypi.org/pypi/make-a-video-pytorch/json (fetched 2026-08-29T10:42:53.049598+00:00, sha 571949cf91d1)
- Data as of 2026-08-30T08:39:29.467469+00:00.