Instructions to use FastVideo/Wan2.1-VSA-T2V-14B-720P-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FastVideo/Wan2.1-VSA-T2V-14B-720P-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FastVideo/Wan2.1-VSA-T2V-14B-720P-Diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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README.md
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--num-frames 81 \
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--fps 16 \
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--guidance-scale
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--VSA-sparsity 0.9 \
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--prompt "A beautiful woman in a red dress walking down a street" \
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--negative-prompt "Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards" \
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--num-frames 81 \
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--num-inference-steps 50 \
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--fps 16 \
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--guidance-scale 4.0 \
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--flow-shift 5.0 \
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--VSA-sparsity 0.9 \
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--prompt "A beautiful woman in a red dress walking down a street" \
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--negative-prompt "Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards" \
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