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:
- f7ecfaf7a98cb3b2b0fa15e1fffe3fac5cce427fcd0674f4b253b974be6ed19f
- Size of remote file:
- 492 MB
- SHA256:
- 893f85bd2f21106f8609bfa86cf466b3f8e8feac9f5c7d46b2bd1d90d98a27e9
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