Image-to-Image
Diffusers
Safetensors
English
SegGuidedDDIMPipeline
diffusion
image-generation
microscopy
microtubule
mask-conditioned
ddim
biology
Instructions to use HTW-KI-Werkstatt/DiffuMT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HTW-KI-Werkstatt/DiffuMT 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("HTW-KI-Werkstatt/DiffuMT", 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
| { | |
| "_class_name": "SegGuidedDDIMPipeline", | |
| "_diffusers_version": "0.35.2", | |
| "eval_dataloader": [ | |
| null, | |
| null | |
| ], | |
| "external_config": [ | |
| null, | |
| null | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "DDIMScheduler" | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNet2DModel" | |
| ] | |
| } | |