Instructions to use EnD-Diffusers/Slime_Tutorial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EnD-Diffusers/Slime_Tutorial with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EnD-Diffusers/Slime_Tutorial", dtype=torch.bfloat16, device_map="cuda") prompt = "deetz1" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- f80ceffe727b089d121fad820652f48f0ead7af320df0c160320aa3fb6a9d5c8
- Size of remote file:
- 3.44 GB
- SHA256:
- e6ab7f5f304579f824e8831becd795be9000edc5ea7475610624dc389e46ee13
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