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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@@ -22,7 +22,7 @@ adapter = MotionAdapter.from_pretrained("wangfuyun/AnimateLCM", torch_dtype=torc
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pipe = AnimateDiffPipeline.from_pretrained("emilianJR/epiCRealism", motion_adapter=adapter, torch_dtype=torch.float16)
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pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config, beta_schedule="linear")
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pipe.load_lora_weights("wangfuyun/AnimateLCM", weight_name="
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pipe.set_adapters(["lcm-lora"], [0.8])
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pipe.enable_vae_slicing()
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pipe = AnimateDiffPipeline.from_pretrained("emilianJR/epiCRealism", motion_adapter=adapter, torch_dtype=torch.float16)
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pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config, beta_schedule="linear")
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pipe.load_lora_weights("wangfuyun/AnimateLCM", weight_name="AnimateLCM_sd15_t2v_lora.safetensors", adapter_name="lcm-lora")
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pipe.set_adapters(["lcm-lora"], [0.8])
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pipe.enable_vae_slicing()
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