Instructions to use whybeyoung/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use whybeyoung/test 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("whybeyoung/test", 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
metadata
license: apache-2.0
language:
- zh
datasets:
- gsdf/EasyNegative
metrics:
- bleu
library_name: diffusers
pipeline_tag: image-to-image
tags:
- code
- music
- art
- chemistry
This is readme for the model