Update README.md

README.md

@@ -13,9 +13,9 @@ new_version: OpenGVLab/InternViT-300M-448px-V2_5
 
 # InternViT-300M-448px
 
-[\[📂 GitHub\]](https://github.com/OpenGVLab/InternVL)  [\[🆕 Blog\]](https://internvl.github.io/blog/)  [\[📜 InternVL 1.0\]](https://arxiv.org/abs/2312.14238)  [\[📜 InternVL 1.5\]](https://arxiv.org/abs/2404.16821) [\[📜 Mini-InternVL\]](https://arxiv.org/abs/2410.16261)
+[\[📂 GitHub\]](https://github.com/OpenGVLab/InternVL)  [\[🆕 Blog\]](https://internvl.github.io/blog/)  [\[📜 InternVL 1.0\]](https://arxiv.org/abs/2312.14238)  [\[📜 InternVL 1.5\]](https://arxiv.org/abs/2404.16821)  [\[📜 InternVL 2.5\]](https://github.com/OpenGVLab/InternVL/blob/main/InternVL2_5_report.pdf)
 
-[\[🗨️ Chat Demo\]](https://internvl.opengvlab.com/)  [\[🤗 HF Demo\]](https://huggingface.co/spaces/OpenGVLab/InternVL)  [\[🚀 Quick Start\]](#quick-start)  [\[📖 中文解读\]](https://zhuanlan.zhihu.com/p/706547971)  [\[📖 Documents\]](https://internvl.readthedocs.io/en/latest/)
+[\[🗨️ Chat Demo\]](https://internvl.opengvlab.com/)  [\[🤗 HF Demo\]](https://huggingface.co/spaces/OpenGVLab/InternVL)  [\[🚀 Quick Start\]](#quick-start)  [\[📖 Documents\]](https://internvl.readthedocs.io/en/latest/)
 
 <div align="center">
   <img width="500" alt="image" src="https://cdn-uploads.huggingface.co/production/uploads/64006c09330a45b03605bba3/zJsd2hqd3EevgXo6fNgC-.png">
@@ -32,7 +32,10 @@ This update primarily focuses on enhancing the efficiency of the vision foundati
 - **Pretrain Dataset:** LAION-en, LAION-zh, COYO, GRIT, COCO, TextCaps, Objects365, OpenImages, All-Seeing, Wukong-OCR, LaionCOCO-OCR, and other OCR-related datasets.
   To enhance the OCR capability of the model, we have incorporated additional OCR data alongside the general caption datasets. Specifically, we utilized PaddleOCR to perform Chinese OCR on images from Wukong and English OCR on images from LAION-COCO.
 
-## Model Usage (Image Embeddings)
+## Quick Start
+
+> \[!Warning\]
+> 🚨 Note: In our experience, the InternViT V2.5 series is better suited for building MLLMs than traditional computer vision tasks.
 
 ```python
 import torch
@@ -55,6 +58,10 @@ pixel_values = pixel_values.to(torch.bfloat16).cuda()
 outputs = model(pixel_values)
 ```
 
+## License
+
+This project is released under the MIT License.
+
 ## Citation
 
 If you find this project useful in your research, please consider citing: