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README.md

@@ -23,12 +23,36 @@ We introduce MathCoder-VL, a series of open-source large multimodal models (LMMs
 |-------------------------------------------------------------------|-----------------------------------------------------------------------|
 |  [Mini-InternVL-Chat-2B-V1-5](https://huggingface.co/OpenGVLab/Mini-InternVL-Chat-2B-V1-5)  |  [MathCoder-VL-2B](https://huggingface.co/MathLLMs/MathCoder-VL-2B)   	|
 |  [InternVL2-8B](https://huggingface.co/OpenGVLab/InternVL2-8B)  |     	[MathCoder-VL-8B](https://huggingface.co/MathLLMs/MathCoder-VL-8B)|
+|  [InternVL2-8B](https://huggingface.co/OpenGVLab/InternVL2-8B)  |     	[FigCodifier-8B](https://huggingface.co/MathLLMs/FigCodifier)|
 
 
 
 ## Usage
 For training and inference code, please refer to [InternVL](https://github.com/OpenGVLab/InternVL).
 
+```
+from datasets import load_dataset
+from PIL import Image
+from io import BytesIO
+
+mm_mathinstruct = load_dataset("MathLLMs/MM-MathInstruct")
+print(mm_mathinstruct)
+
+# show the last image
+img = Image.open(BytesIO(mm_mathinstruct['train'][-1]['image']))
+img.show()
+```
+
+It should print:
+```
+DatasetDict({
+    train: Dataset({
+        features: ['id', 'image', 'question', 'solution', 'image_path'],
+        num_rows: 2871988
+    })
+})
+```
+
 ### Prompt for TikZ Code Generation
 
 ```