Image-to-Image
Diffusers
Safetensors
English
virtual-try-on
diffusion
stable-diffusion
multi-reference
computer-vision
comfyui
gradio
aigc
Instructions to use zhengchong/FastFit-SR-1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zhengchong/FastFit-SR-1024 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("zhengchong/FastFit-SR-1024", 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 and library_name to model card
#1
by nielsr HF Staff - opened
This PR improves the model card by adding the pipeline_tag and library_name to the metadata. This ensures that the model is correctly categorized on the Hub, making it easier for users to discover and leverage the automated code snippets.
- Adds
pipeline_tag: image-to-imagefor better discoverability at https://huggingface.co/models?pipeline_tag=image-to-image. - Adds
library_name: diffusersto enable the automated "how to use" widget, based on the acknowledgement that the code is built ondiffusers.
The existing image-to-image tag has been removed from the tags list to avoid redundancy.
zhengchong changed pull request status to merged