Image-to-Image
Diffusers
Safetensors
English
image-restoration
all-in-one
diffusion
flow-matching
mllm
flux
qwen2.5-vl
siglip2
low-level-vision
Instructions to use David0219/FAPEIR_Uniworld with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use David0219/FAPEIR_Uniworld 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("David0219/FAPEIR_Uniworld", 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
Commit History
-
Update README.md
Verified signature4124617
-
Upload 17 files
Verified signature98b9eed -
Upload added_tokens.json
Verified signatureed2e4f3 -
Upload 7 files
Verified signature524b8cf -
Upload 5 files
Verified signature807f74a -
Upload 5 files
Verified signatureb6cd2ad -
Upload 8 files
Verified signature365ed4a -
Upload 8 files
Verified signature2589bb6 -
Upload 5 files
Verified signature85b07a9 -
Upload 4 files
Verified signature71c534b -
Upload 8 files
Verified signature717f10d -
Delete scheduler
Verified signature9d86d63 -
Delete flux
Verified signature9eee052 -
Create flux
Verified signaturefff2a81 -
Upload scheduler/scheduler_config.json
Verified signature3e82f4e -
initial commit
Verified signature32e0bb7