Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use zrross11/modelOutput with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zrross11/modelOutput with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zrross11/modelOutput", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of a colton face" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- fbb35da5ee3c90567199ca6954ea73da6a04f1647e1c802b2c1744b18c193b24
- Size of remote file:
- 3.44 GB
- SHA256:
- 0db730c54135ef6a00765c83ded7e2091a7cc10f9d1bce67343db8719a13d273
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.