Update README.md

README.md

@@ -41,7 +41,41 @@ To ensure ease of use, the dataset is partitioned into 10 parts. Each part can b
 1. **id**: The unique identifier for the sample.  
 2. **audio_file_path**: The file path for the audio in the dataset.  
 3. **category**: The category of the sample's text.  
-4. **text**: The corresponding text of the audio file.  
+4. **text**: The corresponding text of the audio file.
+
+## Usage Instructions
+
+To use this dataset, download the parts and metadata files as follows:
+
+### Option 1: Manual Download
+Visit the [dataset repository](https://huggingface.co/datasets/llm-lab/SpeechBrown/tree/main) and download all `dataset_partX.zip` files and the `global_metadata.json` file.
+
+### Option 2: Programmatic Download
+Use the `huggingface_hub` library to download the files programmatically:
+
+```python
+from huggingface_hub import hf_hub_download
+from zipfile import ZipFile
+import os
+import json
+
+# Download dataset parts
+zip_file_path1 = hf_hub_download(repo_id="llm-lab/SpeechBrown", filename="dataset_part1.zip", repo_type="dataset")
+zip_file_path2 = hf_hub_download(repo_id="llm-lab/SpeechBrown", filename="dataset_part2.zip", repo_type="dataset")
+# Download other parts...
+
+# Download metadata
+metadata_file_path = hf_hub_download(repo_id="llm-lab/SpeechBrown", filename="global_metadata.json", repo_type="dataset")
+
+for i in range(1, 11):
+    with ZipFile(f'dataset_part{i}.zip', 'r') as zip_ref:
+        zip_ref.extractall(f'dataset_part{i}')
+    os.remove(f'dataset_part{i}.zip')
+
+with open('global_metadata.json', 'r') as f:
+    metadata = json.load(f)
+metadata.keys()
+```
 
 ## Citations
 If you find our paper, code, data, or models useful, please cite the paper: