Instructions to use mit-han-lab/dc-ae-f64c128-mix-1.0-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mit-han-lab/dc-ae-f64c128-mix-1.0-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("mit-han-lab/dc-ae-f64c128-mix-1.0-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
Download diffusion_pytorch_model.safetensors from mit-han-lab/dc-ae-f64c128-mix-1.0-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 2.71 GB
-
https://huggingface.co/mit-han-lab/dc-ae-f64c128-mix-1.0-diffusers/resolve/main/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://mit-han-lab/dc-ae-f64c128-mix-1.0-diffusers/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/mit-han-lab/dc-ae-f64c128-mix-1.0-diffusers/resolve/main/diffusion_pytorch_model.safetensors
2.71 GB
- Xet hash:
- 283f2db96762413901db5a9963e45c35d93d0087628faf72e159817541a8ad75
- Size of remote file:
- 2.71 GB
- SHA256:
- ae11d521da6370b9dec34758f78a6359a3d486b121afb460bd549e8182c518d1
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