Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use roca2357/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use roca2357/output with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("roca2357/output", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- bc607fa23ee88fa45741c64e68c7521ed7674e8c48555762339e26f423c61b65
- Size of remote file:
- 492 MB
- SHA256:
- 5a536a73223d0aad893fd29e3b6095ac9b71ba6dafcb799c88f0abb4f173931f
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