Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use anic87/crc-tumor-normal-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anic87/crc-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/crc-tumor-normal-text", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks tissue-histology-without-tumor" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from anic87/crc-tumor-normal-text: direct link, hf CLI and curl.
- Browser
- Download file 1.36 GB
-
https://huggingface.co/anic87/crc-tumor-normal-text/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://anic87/crc-tumor-normal-text/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anic87/crc-tumor-normal-text/resolve/main/text_encoder/pytorch_model.bin
1.36 GB
- Xet hash:
- db3fca1145fc6c1b046d8ffb6c3cc1915937356da299e60c52f4b81fef602100
- Size of remote file:
- 1.36 GB
- SHA256:
- 858cd76f988e5b1c132d1e17210716349cb2d8323142dd0894195677a6e14c28
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