Instructions to use warp-ai/wuerstchen-prior-model-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use warp-ai/wuerstchen-prior-model-base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("warp-ai/wuerstchen-prior-model-base", 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
Download diffusion_pytorch_model.bin from warp-ai/wuerstchen-prior-model-base: direct link, hf CLI and curl.
- Browser
- Download file 3.97 GB
-
https://huggingface.co/warp-ai/wuerstchen-prior-model-base/resolve/main/diffusion_pytorch_model.bin
- Command line
-
hf download hf://warp-ai/wuerstchen-prior-model-base/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/warp-ai/wuerstchen-prior-model-base/resolve/main/diffusion_pytorch_model.bin
3.97 GB
- Xet hash:
- be85e6d00ff1b80d9fa6d796a0e8094883dfd20a943cd9db497023a0ec9f4354
- Size of remote file:
- 3.97 GB
- SHA256:
- eabdf44642d19b7483db26104fb37d1d7996e3dc9b71b07ae806523e0f6f3474
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