Unconditional Image Generation
Diffusers
Safetensors
CDMDiTPipeline
zoomldm
cdm
dit
histopathology
brca
custom-pipeline
Instructions to use BiliSakura/ZoomLDM-CDM-brca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/ZoomLDM-CDM-brca with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/ZoomLDM-CDM-brca", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add files using upload-large-folder tool
Browse files
README.md
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url: demo_images/output.jpeg
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# BiliSakura/ZoomLDM-CDM-brca
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Diffusers-style wrapped **CDM (DiT)** checkpoint for BRCA, converted from ZoomLDM `cdm_dit` training outputs.
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url: demo_images/output.jpeg
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> [!WARNING] we do not have a full checkpoint conversion validation, if you encounter pipeline loading failure and unsidered output, please contact me via bili_sakura@zju.edu.cn
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# BiliSakura/ZoomLDM-CDM-brca
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Diffusers-style wrapped **CDM (DiT)** checkpoint for BRCA, converted from ZoomLDM `cdm_dit` training outputs.
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