Instructions to use igorshmel/hatching-style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use igorshmel/hatching-style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("igorshmel/hatching-style", 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 text_encoder/pytorch_model.bin from igorshmel/hatching-style: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/igorshmel/hatching-style/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://igorshmel/hatching-style@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/igorshmel/hatching-style/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- f49d8178589cd819de2ad481efd3d5616cc2b3bf3acff03d657b108715571e1f
- Size of remote file:
- 492 MB
- SHA256:
- a13a83d753e06812c6db541a5f6c1cfbddef7dcad177d3a4cdccf5e432611ec2
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