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/scheduler.bin from anic87/crc-tumor-text: direct link, hf CLI and curl.
- Browser
- Download file 559 Bytes
-
https://huggingface.co/anic87/crc-tumor-text/resolve/main/checkpoint-500/scheduler.bin
- Command line
-
hf download hf://anic87/crc-tumor-text/checkpoint-500/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/anic87/crc-tumor-text/resolve/main/checkpoint-500/scheduler.bin
559 Bytes
- Xet hash:
- 1ba4c849642e05fe24a933996bc183ff90f8ab961d256bb711c9a6bb43ec3112
- Size of remote file:
- 559 Bytes
- SHA256:
- c78bdf9fb4e265639c0fa7f35aee3409d84a5fad00aa5616450c323e0f2948e6
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