ImaginAIry
Pythonic AI generation of images and videos
Research code for real-time interactive video via diffusion distillation.
Causal-Forcing is an open-source video project by thu-ml (thu-ml/Causal-Forcing on GitHub). It has 987 GitHub stars and 57 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 3 October 2026.
Understand the causal forcing distillation method.
Interactive video research needs strong GPUs.
Set up the official implementation.
Run the experiments from the paper.
Published at a top ML venue.
Makes diffusion models much faster.
Aims for interactive video generation.
Generates video frame-by-frame causally.
Reproduces the paper's results.
Open for research use.
Download the source and move into the project folder.
git clone https://github.com/thu-ml/Causal-Forcing.git
cd Causal-ForcingEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command โ Docker, pip, npm, or a binary release.
# see README for the exact launch commandApache 2.0 licensed โ free for research and commercial use.
Research-grade GPUs โ check the README for specifics.
Research code reproducing an ICML 2026 paper.
Real-time interactive generation is the research goal.
Linked from the project page โ ICML 2026.
Pythonic AI generation of images and videos
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Free and open โ grab the source, star the repo, and start creating.