Refine readme instructions

README.md

@@ -15,6 +15,9 @@ viewer: false
 This dataset is associated with DiffVox, a novel and interpretable model designed for matching vocal effects in music production. DiffVox integrates parametric equalisation, dynamic range control, delay, and reverb using efficient differentiable implementations, enabling gradient-based optimisation for parameter estimation. The vocal presets contained within this dataset were retrieved from two collections: 70 tracks from MedleyDB and 365 tracks from a private collection. This work lays the foundation for future research in vocal effects modelling and automatic mixing.
 
 This dataset is a clone of a subset of the [diffvox](https://github.com/SonyResearch/diffvox/) repository, containing a collection of vocal effect presets derived from a proprietary multitrack dataset.
+It contains the minimal set of files for loading the presets.
+You can load this subset module into your Huggingface Space using the Huggingface API. 
+For concrete examples, please refer to our [demo](https://huggingface.co/spaces/yoyolicoris/diffvox).
 
 ## Links
 - Paper: [DiffVox: A Differentiable Model for Capturing and Analysing Vocal Effects Distributions](https://arxiv.org/abs/2504.14735)
@@ -29,7 +32,8 @@ The [modules/](modules/) contains differentiable effects implemented in PyTorch
 
 ## Sample Usage
 
-For concrete examples of how to use the dataset and its associated code, please refer to the original GitHub repository. Below is a quick start example demonstrating how to set up the environment and run the retrieval process on a single track:
+For details on how we created the dataset, please refer to the original GitHub repository. 
+Below is a quick start example demonstrating how to set up the environment and run the retrieval process on a single track:
 
 First, install the required Python packages by cloning the original repository and installing its requirements:
 ```bash