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:
- a7b5f070110c7fdda2f3a3e9519d8aec6156630cae56063b7a3d53d65095428f
- Size of remote file:
- 1.36 GB
- SHA256:
- f3135442e90483a0b8bcf65e10cac6dd789cc27145a65c441bb18a6149210897
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