Instructions to use NisargUpadhyay/ImageSuperResolution-replication with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NisargUpadhyay/ImageSuperResolution-replication 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("NisargUpadhyay/ImageSuperResolution-replication", 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
File size: 305 Bytes
ead48bd | 1 2 3 4 5 6 7 8 | {
"checkpoint_step": 150000,
"experiment_dir": "/DATA2/b23cs1037/experiments/dit4sr-replication",
"experiment_name": "dit4sr-replication",
"source_dir": "/DATA2/b23cs1037/experiments/dit4sr-replication/checkpoint-150000",
"source_name": "checkpoint-150000",
"uploaded_only_transformer": true
} |