Instructions to use SidXXD/44 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/44 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/44", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <v1*> person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- faead14b302404e7c2a77710f962e80b0a7ae32c03fc7bd15962dc37806c9c93
- Size of remote file:
- 76.7 MB
- SHA256:
- 724e9f0ee0885156c66dd8b27965466fd5c749745e79d18e124d2b881a1b7a69
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