Image-to-Image
Diffusers
Safetensors
ZoomLDMPipeline
zoomldm
histopathology
brca
latent-diffusion
custom-pipeline
arxiv:2411.16969
Instructions to use BiliSakura/ZoomLDM-brca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/ZoomLDM-brca with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/ZoomLDM-brca", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| { | |
| "use_checkpoint": true, | |
| "use_fp16": true, | |
| "image_size": 64, | |
| "in_channels": 3, | |
| "out_channels": 3, | |
| "model_channels": 192, | |
| "attention_resolutions": [ | |
| 8, | |
| 4, | |
| 2 | |
| ], | |
| "num_res_blocks": 2, | |
| "channel_mult": [ | |
| 1, | |
| 2, | |
| 3, | |
| 5 | |
| ], | |
| "num_heads": 1, | |
| "use_spatial_transformer": true, | |
| "transformer_depth": 1, | |
| "context_dim": 512 | |
| } |