Instructions to use dhanushkaha/diffusion_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dhanushkaha/diffusion_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dhanushkaha/diffusion_model", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.safetensors from dhanushkaha/diffusion_model: direct link, hf CLI and curl.
- Browser
- Download file 1.22 GB
-
https://huggingface.co/dhanushkaha/diffusion_model/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://dhanushkaha/diffusion_model/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/dhanushkaha/diffusion_model/resolve/main/vae/diffusion_pytorch_model.safetensors
1.22 GB
- Xet hash:
- 3e6084a7831fd989ab9e7a6a88745fce55823b69b6ea6832ff6c5cc08fee958f
- Size of remote file:
- 1.22 GB
- SHA256:
- 9d6a233ff6fd5ccb9f76fd99618d73369c52dd3d8222376384d0e601911089e8
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