Create README.md

README.md

@@ -0,0 +1,32 @@
+# IVT-LR (Qwen2-VL)
+
+## Overview
+
+This model was presented in the paper [Reasoning in the Dark: Interleaved Vision-Text Reasoning in Latent Space](https://huggingface.co/papers/2510.12603).
+
+Interleaved Vision-Text Latent Reasoning (IVT-LR) is the first VLM framework that unifies textual and visual representations in the latent space and implements multimodal latent reasoning. Specifically, IVT-LR represents each reasoning step by combining two implicit parts: **latent text** and **latent vision**. We further introduce a progressive multi-stage training strategy to enable MLLMs to perform the above multimodal latent reasoning steps.
+
+---
+
+## Usage
+
+This repository provides pretrained Qwen2-VL models for IVT-LR on **M3CoT** and **ScienceQA** datasets.
+
+To see detailed usage, including inference code and scripts for training, please refer to the [GitHub repository](https://github.com/ModalityDance/IVT-LR).
+
+---
+
+### Download Models
+
+You can download the models directly from Hugging Face using `huggingface_hub`:
+
+```python
+from huggingface_hub import hf_hub_download
+
+# Download Qwen2-VL model trained on M3CoT
+qwen_m3cot_path = hf_hub_download("ModalityDance/IVTLR_QWEN_M3COT", "model.pth")
+
+# Download Qwen2-VL model trained on ScienceQA
+qwen_sqa_path = hf_hub_download("ModalityDance/IVTLR_QWEN_SQA", "model.pth")
+```
+