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
- Draw Things
- DiffusionBee
- Xet hash:
- fd1d1e62a2dea3947187bd0087f2783009e0b8e01683bc401d34724c21a7a109
- Size of remote file:
- 6.88 GB
- SHA256:
- 25bff5330aad9a700ad2eb2a762341d490be0b0f1b85275c134552e6b19f5fca
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