Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use anic87/pcam-tumor-normal-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anic87/pcam-tumor-normal-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-normal-text", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks noncancerous-pathology-tissue" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from anic87/pcam-tumor-normal-text: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/anic87/pcam-tumor-normal-text/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://anic87/pcam-tumor-normal-text/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anic87/pcam-tumor-normal-text/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 2254c7b731fbb1ffd35920ebc4c1bf3e13673b18dce127e81323fd7c07891a7d
- Size of remote file:
- 492 MB
- SHA256:
- 400888144763681558d6de31871b311f9bcdfa23e1e239f58ef21fbc9eee5c40
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