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
Commit History
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Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (#2)
- Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (41b0dea2d2e157f6a18ce9441a62958b0f77a232)c95929c
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Upload the concept hatching_style embeds and token
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initial commit
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