Instructions to use Linaqruf/hitokomoru-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Linaqruf/hitokomoru-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Linaqruf/hitokomoru-diffusion", 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 vae/diffusion_pytorch_model.bin from Linaqruf/hitokomoru-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/Linaqruf/hitokomoru-diffusion/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Linaqruf/hitokomoru-diffusion@refs/pr/1/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Linaqruf/hitokomoru-diffusion/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- fae4a77d272c8e4204b11a3014fa263622778b8c2e3f53a7ea6c77abcd425225
- Size of remote file:
- 335 MB
- SHA256:
- 1ced03dc0cf388fc19c84959dcc12a4943f2d330ec2211a9bdf2918d3bf7ec4c
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