Update README.md

README.md

@@ -29,7 +29,7 @@ This dataset demonstrates several advantages over its counterparts:
 The OmniCorpus contains three sections:
 
 - **OmniCorpus-CC**: processed from dumps in Common Crawl from 2013 to Nov./Dec. 2023.
-- **OmniCorpus-CW**: sourced from Chinese internet resources, will be availiable in [OpenDataLab](https://opendatalab.com/) platform.
+- **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.
@@ -129,7 +129,7 @@ def extract_frames_with_hls(youtube_id, timestamps, output_dir='frames'):
         pool.starmap(extract_frame, tasks)
 
 if __name__ == "__main__":
-    fextract_frames_with_hls("1xGiPUeevCM", [19.000000, 23.000000, 28.000000, 32.000000, 45.000000, 54.000000, 57.000000, 67.000000])
+    extract_frames_with_hls("1xGiPUeevCM", [19.000000, 23.000000, 28.000000, 32.000000, 45.000000, 54.000000, 57.000000, 67.000000])
 ```
 
 # License