Update README.md

README.md

@@ -144,34 +144,54 @@ INTERCHART supports both **visual** and **table-based** evaluation modes.
 
 ## 🚀 Usage
 
-### Load from Hugging Face
+### 🔐 Access & Download Instructions
 
-```python
-from datasets import load_dataset
+Use an **access token** as your Git credential when cloning or pushing to the repository.
 
-dataset = load_dataset("interchart/interchart", name="DECAF")
-print(dataset["train"][0])
-````
+1. **Install Git LFS**  
+   Download and install from [https://git-lfs.com](https://git-lfs.com).  
+   Then run:
+```
+
+git lfs install
 
-Available subsets:
+```
 
-* `"DECAF"`
-* `"SPECTRA"`
-* `"STORM"`
+2. **Clone the dataset repository**  
+When prompted for a password, use your **Hugging Face access token** with *write permissions*.  
+You can generate one here: [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens)
 
-Each entry contains:
+```
+
+git clone [https://huggingface.co/datasets/interchart/Interchart](https://huggingface.co/datasets/interchart/Interchart)
+
+```
+
+3. **Clone without large files (LFS pointers only)**  
+If you only want lightweight clones without downloading all image data:
+```
+
+GIT_LFS_SKIP_SMUDGE=1 git clone [https://huggingface.co/datasets/interchart/Interchart](https://huggingface.co/datasets/interchart/Interchart)
 
-```json
-{
-  "id": "DECAF_00123",
-  "image_path": "DECAF/simple/chart_123.png",
-  "question": "What is the highest bar value for 2020?",
-  "answer": "45.6",
-  "question_type": "comparison",
-  "subset": "DECAF"
-}
 ```
 
+4. **Alternative: use the Hugging Face CLI**
+Make sure the CLI is installed:
+```
+
+pip install -U "huggingface_hub[cli]"
+
+```
+
+Then download directly:
+```
+
+hf download interchart/Interchart --repo-type=dataset
+
+```
+
+
+
 ---
 
 ## 🔍 Citation