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ImaginAIry
Pythonic AI generation of images and videos
★ 8,2 mil estrelasMIT
Ver o guia →Causal-Forcing é um projeto de vídeo de código aberto de thu-ml (thu-ml/Causal-Forcing no GitHub). Tem 987 estrelas no GitHub e 57 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 3 de outubro de 2026.
Research code for real-time interactive video via diffusion distillation.
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 — Docker, pip, npm, or a binary release.
# see README for the exact launch commandApache 2.0 licensed — free for research and commercial use.
Research-grade GPUs — 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 — ICML 2026.
Pythonic AI generation of images and videos
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Source code for no-cost AI video upscaler utility.
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One model, video and audio generated in sync together.
Turn any topic into a brainrot-style explainer video from AI personalities.
Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.