Datasets:

jamescalam
/

youtube-transcriptions

Tasks:

Question Answering

Visual Question Answering

Modalities:

Formats:

Sub-tasks:

document-retrieval

Languages:

Size:

Tags:

Libraries:

License:

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jamescalam commited on Oct 21, 2022

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@@ -35,7 +35,7 @@ task_ids:
 - visual-question-answering
 ---
-The YouTube transcriptions dataset contains technical tutorials (currently only from [YouTube.com/c/JamesBriggs](https://www.youtube.com/c/jamesbriggs)) transcribed using [OpenAI's Whisper](https://huggingface.co/openai/whisper-large) (large). Each row represents roughly a sentence-length chunk of text alongside the video URL and timestamp.
 Note that each item in the dataset contains just a short chunk of text. For most use cases you will likely need to merge multiple rows to create more substantial chunks of text, if you need to do that, this code snippet will help:

 - visual-question-answering
 ---
+The YouTube transcriptions dataset contains technical tutorials (currently from [James Briggs](https://www.youtube.com/c/jamesbriggs), [Daniel Bourke](https://www.youtube.com/channel/UCr8O8l5cCX85Oem1d18EezQ), and [AI Coffee Break](https://www.youtube.com/c/aicoffeebreak)) transcribed using [OpenAI's Whisper](https://huggingface.co/openai/whisper-large) (large). Each row represents roughly a sentence-length chunk of text alongside the video URL and timestamp.
 Note that each item in the dataset contains just a short chunk of text. For most use cases you will likely need to merge multiple rows to create more substantial chunks of text, if you need to do that, this code snippet will help: