Instructions to use aroopchandra/sd-vae-ft-mse-original with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aroopchandra/sd-vae-ft-mse-original with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aroopchandra/sd-vae-ft-mse-original", 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.ckpt from aroopchandra/sd-vae-ft-mse-original: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/aroopchandra/sd-vae-ft-mse-original/resolve/main/diffusion_pytorch_model.ckpt
- Command line
-
hf download hf://aroopchandra/sd-vae-ft-mse-original/diffusion_pytorch_model.ckpt
-
curl -L -o diffusion_pytorch_model.ckpt https://huggingface.co/aroopchandra/sd-vae-ft-mse-original/resolve/main/diffusion_pytorch_model.ckpt
335 MB
- Xet hash:
- 91bafaadd7376203817f12570ba888c645651dd5a8f77b85e08ee578c1df8bac
- Size of remote file:
- 335 MB
- SHA256:
- c6a580b13a5bc05a5e16e4dbb80608ff2ec251a162311590c1f34c013d7f3dab
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