Instructions to use dn6/RFDiffusion-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dn6/RFDiffusion-3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dn6/RFDiffusion-3", 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 mpnn/diffusion_pytorch_model.safetensors from dn6/RFDiffusion-3: direct link, hf CLI and curl.
- Browser
- Download file 6.65 MB
-
https://huggingface.co/dn6/RFDiffusion-3/resolve/main/mpnn/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://dn6/RFDiffusion-3/mpnn/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/dn6/RFDiffusion-3/resolve/main/mpnn/diffusion_pytorch_model.safetensors
6.65 MB
- Xet hash:
- 10063307376dc4918d88063991972106f15e6dea93bedfd452fd971cc962b195
- Size of remote file:
- 6.65 MB
- SHA256:
- 6f94bbbaa904c3554d3b10397dce3c90e01adb725fd80e3275ff48f11cc4745f
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