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README.md
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pipeline_tag: image-to-video
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---
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# AnimateLCM-I2V for Fast Image-conditioned Video Generation in 4 steps.
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For more details, please refer to our [[paper](https://arxiv.org/abs/2402.00769)] | [[code](https://github.com/G-U-N/AnimateLCM)] | [[proj-page](https://animatelcm.github.io/)] | [[civitai](https://civitai.com/models/310920/animatelcm-i2v-fast-image-to-video-generation)].
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63e9e92f20c109718713f5eb/KCwSoZCdxkkmtDg1LuXsP.mp4"></video>
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---
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pipeline_tag: image-to-video
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license: mit
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datasets:
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- openai/MMMLU
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language:
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- am
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metrics:
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- accuracy
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base_model:
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- black-forest-labs/FLUX.1-dev
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new_version: black-forest-labs/FLUX.1-dev
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library_name: adapter-transformers
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tags:
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- chemistry
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---
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# AnimateLCM-I2V for Fast Image-conditioned Video Generation in 4 steps.
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For more details, please refer to our [[paper](https://arxiv.org/abs/2402.00769)] | [[code](https://github.com/G-U-N/AnimateLCM)] | [[proj-page](https://animatelcm.github.io/)] | [[civitai](https://civitai.com/models/310920/animatelcm-i2v-fast-image-to-video-generation)].
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63e9e92f20c109718713f5eb/KCwSoZCdxkkmtDg1LuXsP.mp4"></video>
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