Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use anic87/poor_well with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anic87/poor_well with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("anic87/poor_well", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks poorly-differentiated-adenocarcinoma" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f30d5f17563629fd9bafa2448c0d3694d66c4574bbf3b550f00f3b14ff38a413
- Size of remote file:
- 3.44 GB
- SHA256:
- aa48d933e6dc60b444d886c470dc0c26974fd1dc87bfcb2c0811f9cfb5dc3d2a
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