Instructions to use ossaili/arch_diffusion_1400 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ossaili/arch_diffusion_1400 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ossaili/arch_diffusion_1400", 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 unet/diffusion_pytorch_model.bin from ossaili/arch_diffusion_1400: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/ossaili/arch_diffusion_1400/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://ossaili/arch_diffusion_1400/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/ossaili/arch_diffusion_1400/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- 0cc05098da2e0fdf1d61b92d82239b4a016601bd2db807218b94269b1abc3a42
- Size of remote file:
- 3.46 GB
- SHA256:
- 81b71ec1982f6171c225688cd513a1c5327e33430257aa8b5d61a87cefe6adc8
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