Instructions to use Erland/tiny-wan2.1-t2v-debug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Erland/tiny-wan2.1-t2v-debug with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Erland/tiny-wan2.1-t2v-debug", 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
Add tiny Wan debug pipeline
Browse files
README.md
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```python
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from diffusers import WanPipeline
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pipe = WanPipeline.from_pretrained("
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pipe.set_progress_bar_config(disable=True)
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frames = pipe(
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prompt="debug prompt",
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```python
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from diffusers import WanPipeline
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pipe = WanPipeline.from_pretrained("Erland/tiny-wan2.1-t2v-debug")
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pipe.set_progress_bar_config(disable=True)
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frames = pipe(
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prompt="debug prompt",
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transformer/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:8a1d4ba7feaeb6a600e87f5c8e0638a6b436a2a0e4414553aa608975b9e993f4
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size 102760
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