Instructions to use gvecchio/MatFuse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gvecchio/MatFuse with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gvecchio/MatFuse", 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 condition_encoder/diffusion_pytorch_model.safetensors from gvecchio/MatFuse: direct link, hf CLI and curl.
- Browser
- Download file 2.23 MB
-
https://huggingface.co/gvecchio/MatFuse/resolve/main/condition_encoder/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://gvecchio/MatFuse/condition_encoder/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/gvecchio/MatFuse/resolve/main/condition_encoder/diffusion_pytorch_model.safetensors
2.23 MB
- Xet hash:
- 79312d753de295819b0eb0c0f90dc1be7a80bb9991c657b089da3097db89d237
- Size of remote file:
- 2.23 MB
- SHA256:
- 1bf932008656551c46a064549570965c19c48539c9e6d5a54c2a40a6414518cb
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