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
Download checkpoint-500/optimizer.bin from anic87/crc-tumor-text: direct link, hf CLI and curl.
- Browser
- Download file 9.65 GB
-
https://huggingface.co/anic87/crc-tumor-text/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://anic87/crc-tumor-text/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/anic87/crc-tumor-text/resolve/main/checkpoint-500/optimizer.bin
9.65 GB
- Xet hash:
- d56b9504333b550ec46cb15a039f9690680eeb134d5d371e00ae44be5726ca26
- Size of remote file:
- 9.65 GB
- SHA256:
- b72a9101418d6fa6ab8782a2ab731cf5d79ed3341d015ca5df645ed5a491ddd8
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