Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use JwonP/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JwonP/model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JwonP/model", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks bowl" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 35fd1c34e9711c67e43fcf0100a3a0f325ec892740ad8e29cb0a62307e52182c
- Size of remote file:
- 1.36 GB
- SHA256:
- 5c46199d0a4d03e0c05554d5a65e81cf8c3b2dba0464a866ef48c3ed954f930b
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