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README.md

@@ -15,10 +15,12 @@ We released [🤗 InternVL-Chat-V1-1](https://huggingface.co/OpenGVLab/InternVL-
 As shown in the figure below, we connected our InternViT-6B to LLaMA2-13B through a simple MLP projector. Note that the LLaMA2-13B used here is not the original model but an internal chat version obtained by incrementally pre-training and fine-tuning the LLaMA2-13B base model for Chinese language tasks. Overall, our model has a total of 19 billion parameters.
 
 <p align="center">
-  <img src="https://cdn-uploads.huggingface.co/production/uploads/64119264f0f81eb569e0d569/HD29tU-g0An9FpQn1yK8X.png" style="width: 75%;">
+    <img src="https://cdn-uploads.huggingface.co/production/uploads/64119264f0f81eb569e0d569/HD29tU-g0An9FpQn1yK8X.png" style="width: 75%;">
 </p>
 
-In this version, we explored increasing the resolution to 448 × 448, enhancing OCR capabilities, and improving support for Chinese conversations. Since the 448 × 448 input image generates 1024 visual tokens after passing through the ViT, leading to a significant computational burden, we use a pixel shuffle operation to reduce the 1024 tokens to 256 tokens.
+In this version, we explored increasing the resolution to 448 × 448, enhancing OCR capabilities, and improving support for Chinese conversations. Since the 448 × 448 input image generates 1024 visual tokens after passing through the ViT, leading to a significant computational burden, we use a pixel shuffle (unshuffle) operation to reduce the 1024 tokens to 256 tokens.
+
+For more detailed information about this model, please read our [blog](https://internvl.github.io/blog/2024-01-24-InternVL-1.1/).
 
 ## Examples
 
@@ -72,6 +74,8 @@ This model can also conduct an in-depth analysis of AAAI's official website and
 |     MMB-CN<sub>test</sub>      |     63.6     |        61.9        |        64.0        |        70.3        |
 |   MMVet<sub>GPT-4-0613</sub>   |     35.4     |        33.7        |        36.7        |        46.7        |
 
+- Note that we use the [official evaluation server](https://huggingface.co/spaces/whyu/MM-Vet_Evaluator) to test the MMVet scores, with `GPT-4-0613` serving as the judge model. Using different versions of GPT-4 as the judge can result in significant score variations.
+
 Here, we have conducted only a simple performance comparison. For more detailed performance information and additional evaluation metrics, please refer to our performance summary table.
 
 ## Quick Start