Instructions to use JiongzeYu/SparkVSR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JiongzeYu/SparkVSR with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JiongzeYu/SparkVSR", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add metadata and improve model card for SparkVSR
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community science team.
I've opened this PR to improve the metadata and documentation for SparkVSR. Specifically, I have:
- Added the
pipeline_tag: image-to-imageto ensure the model is categorized correctly. - Added
library_name: diffusersbased on the configuration files in the repository. - Linked the
base_model(CogVideoX1.5-5B-I2V). - Included the detailed setup and inference instructions from your GitHub README to make the model card more informative.
These changes will help users discover and use your model more easily on the Hub!