This PR significantly enhances the model card for **SimVQ** by adding essential information and improving its discoverability on the Hugging Face Hub.
Key updates include:
- **Metadata**: Added `pipeline_tag: image-to-image` to categorize the model for relevant tasks. The existing `license: mit` is retained.
- **Model Description**: Incorporated a summary of the model from the paper's abstract, explaining its purpose and approach.
- **Links**: Provided direct links to the scientific paper ([Addressing Representation Collapse in Vector Quantized Models with One Linear Layer](https://huggingface.co/papers/2411.02038)) and the official GitHub repository (https://github.com/youngsheen/SimVQ).
- **Key Results**: Integrated crucial visual and quantitative data from the GitHub README, including the SimVQ algorithm diagram, detailed quantitative comparison tables for image and audio reconstruction, and visualization examples of reconstructed images and audio. All relative image paths …
