Instructions to use wangfuyun/AnimateLCM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangfuyun/AnimateLCM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wangfuyun/AnimateLCM", 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
Update README.md
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README.md
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@@ -29,7 +29,7 @@ pipe.enable_vae_slicing()
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pipe.enable_model_cpu_offload()
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output = pipe(
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prompt="A space rocket with trails of smoke
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negative_prompt="bad quality, worse quality, low resolution",
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num_frames=16,
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guidance_scale=2.0,
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pipe.enable_model_cpu_offload()
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output = pipe(
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prompt="A space rocket shaped as a fish with trails of smoke everywhere all the tıme launching into space from the desert, 4k, high resolution",
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negative_prompt="bad quality, worse quality, low resolution",
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num_frames=16,
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guidance_scale=2.0,
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