update the read me with example to load the dataset

L2T-NeurIPS-2023.py

@@ -54,6 +54,7 @@ reviews = ['Deliciously fragrant xxx',
 
 
 _REPO = f"https://huggingface.co/datasets/{USERNAME}/{REPO_NAME}/resolve/main/"
+_REPO = "https://huggingface.co/datasets/Dakhoo/L2T-NeurIPS-2023/resolve/main/"
 if LOCAL:
     _REPO = f"/Users/alka/Devel/L2T-NeurIPS-2023"
 

README.md

@@ -26,9 +26,19 @@ We obtained fine-grained flavor annotations on a subset by conducting a wine-tas
 with 256 participants who were asked to rank wines based on their similarity in flavor,
 resulting in more than 5k pairwise flavor distances.
 
-### Languages
+## Hugging Face Datasets
+
+use the following command to load the dataset in Hugging Face Datasets library:
+
+```python
+dataset = load_dataset('Dakhoo/L2T-NeurIPS-2023', 'vintages')
+dataset = load_dataset('Dakhoo/L2T-NeurIPS-2023', 'napping_participants')
+dataset = load_dataset('Dakhoo/L2T-NeurIPS-2023', 'wt_session')
+dataset = load_dataset('Dakhoo/L2T-NeurIPS-2023', 'small')
+dataset = load_dataset('Dakhoo/L2T-NeurIPS-2023', 'all')
+```
+
 
-English
 
 ## Dataset Structure
 
@@ -72,13 +82,7 @@ The dataset contains the file metadata.zip, consisting of the files participants
 
 ## Dataset Creation
 
-### All Images Dataset
-
-1) Unzip all the chunk_*.zip files
-	2) Copy the script create_all_images_dataset.sh to the output_images/ directory
-	3) Execute chmod +x create_all_images_dataset.sh
-	4) Execute ./create_all_images_dataset.sh
-
+Follow the instructions in this [link](https://thoranna.github.io/learning_to_taste/) to create the dataset.
 
 ## Additional Information