Instructions to use PANDATREE/BRIDGE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PANDATREE/BRIDGE 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("PANDATREE/BRIDGE", 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
Add pipeline tag, library name, and paper link
#1
by nielsr HF Staff - opened
This PR adds pipeline_tag: image-to-image and library_name: diffusers to the metadata for better discoverability and integration on the Hub. It also adds a link to the paper page in the README content.
PANDATREE changed pull request status to merged