Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use anic87/pcam-tumor-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anic87/pcam-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/pcam-tumor-text", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks tumor-pathology-tissue" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f68cc4bcd2aa641ef9c94900bcb40fd129f803d3a752a4960377f6dbe708d466
- Size of remote file:
- 492 MB
- SHA256:
- 641d0425448f345be126a95af86a55829ec388884974d4e7d5436741ebd96570
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