Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use Loyola/diffusionmodel4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Loyola/diffusionmodel4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Loyola/diffusionmodel4", dtype=torch.bfloat16, device_map="cuda") prompt = "A Loyolatic painting" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- de714a6f934b2385b59a989ec4c4b70870791d6c001a26f34e03e8ffe6b83cb8
- Size of remote file:
- 6.88 GB
- SHA256:
- b3c55e988d7f78cb1eb01c428b68fa672069809185a6dd26bec5aca6fd8c453b
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