Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use anic87/crc-tumor-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anic87/crc-tumor-text 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/crc-tumor-text", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks tumor-tissue-histology" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 959cf9c47038488b5a286272a2c5fda902152e5b768b13bb0eab5360d90f0acd
- Size of remote file:
- 9.65 GB
- SHA256:
- 1b51dd432b13ae414c83b1523c0e6f681936c9001074783fb71a1e70b0fccf69
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