Instructions to use ahmedfaiyaz/OkkhorDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ahmedfaiyaz/OkkhorDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ahmedfaiyaz/OkkhorDiffusion", 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 diffusion_pytorch_model.bin from ahmedfaiyaz/OkkhorDiffusion: direct link, hf CLI and curl.
- Browser
- Download file 114 MB
-
https://huggingface.co/ahmedfaiyaz/OkkhorDiffusion/resolve/main/diffusion_pytorch_model.bin
- Command line
-
hf download hf://ahmedfaiyaz/OkkhorDiffusion/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/ahmedfaiyaz/OkkhorDiffusion/resolve/main/diffusion_pytorch_model.bin
114 MB
- Xet hash:
- 73b91b6dad8b79c4c0a22265fd76d206dadd7d2071f795b45d820dcb30ceeddc
- Size of remote file:
- 114 MB
- SHA256:
- 32e64233a65d146c0453795c22b284444d595a249bf3ab9f485ce1f0a798950e
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