Update README.md

README.md

@@ -18,7 +18,7 @@ This is the repository of OmniCorpus-YT, which contains 10 million image-text in
 - Repository: https://github.com/OpenGVLab/OmniCorpus
 - Paper: https://arxiv.org/abs/2406.08418
 
-OmniCorpus dataset is a large-scale image-text interleaved dataset, which pushes the boundaries of scale and diversity by encompassing **8.6 billion images** interleaved with **1,696 text tokens** from diverse sources, significantly surpassing previous datasets.
+OmniCorpus dataset is a large-scale image-text interleaved dataset, which pushes the boundaries of scale and diversity by encompassing **8.6 billion images** interleaved with **1,696 billion text tokens** from diverse sources, significantly surpassing previous datasets.
 This dataset demonstrates several advantages over its counterparts:
 
 1. **Larger data scale:** Our dataset is 1.7 times larger in images and 12.5 times larger in texts compared to the previously largest multimodal dataset, LAION-5B, while maintaining excellent data quality.
@@ -33,7 +33,7 @@ The OmniCorpus contains three sections:
 - **OmniCorpus-CW**: sourced from Chinese internet resources, will be availiable on [OpenDataLab](https://opendatalab.com/) platform.
 - **OmniCorpus-YT**: samples Youtube video frames as images and collects subtitles as texts.
 
-Code for pre-training, evaluating, main body extracting, and filtering have been released in the official [repository](https://github.com/OpenGVLab/OmniCorpus). A pre-trained model is availiable [here](). We are processing and uploading the rest data sections as soon as possible.
+Code for pre-training, evaluating, main body extracting, and filtering have been released in the official [repository](https://github.com/OpenGVLab/OmniCorpus). A pre-trained model is availiable [here](https://huggingface.co/Qingyun/OmniCorpus-InternVL).
 
 # Usages