Instructions to use shahp7575/oxford_flowers_sample_diffused with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use shahp7575/oxford_flowers_sample_diffused with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("shahp7575/oxford_flowers_sample_diffused", 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.bin from shahp7575/oxford_flowers_sample_diffused: direct link, hf CLI and curl.
- Browser
- Download file 74.3 MB
-
https://huggingface.co/shahp7575/oxford_flowers_sample_diffused/resolve/main/diffusion_pytorch_model.bin
- Command line
-
hf download hf://shahp7575/oxford_flowers_sample_diffused/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/shahp7575/oxford_flowers_sample_diffused/resolve/main/diffusion_pytorch_model.bin
74.3 MB
- Xet hash:
- 69a71a228363b5a7a56459fb86703c68e61aca5380c3af7a544f43e8256a5faf
- Size of remote file:
- 74.3 MB
- SHA256:
- 1a26fb36f294806835a1a9a4713496e89b1e93b2640b3ae5cb801ddcbb9bff44
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