#Optimizing Custom GPT Models for In-depth Summarization of Video Transcripts

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placid canyon
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I created a customized GPT within the GPT-builder UI with the main goal to provide more then a standard summary, thus literally the most important takeaways, key points, quotes or ingredients that stood out and embody the red line of the story sort of speak.

When I upload a file in .txt-file-format (or a .json, .tsv, vtt) within my ChatGPT4 customized GPT, containing a transcript of a MP4-video, then ChatGPT provides a shallow summary.

I have tried everything, from uploading the transcripts in different formats, rewrite the GPT-instructions in hundreds different ways, styles, e.g. using markdown, bullet points, all without any success.

Its also very difficult for me to create a template withing the instructions or a knowledge file that will met this goal, at least with my skillset. I wonder how I am able to use the 8000 characters as instructions in my advantage for this customized GPT.

I think its because ChatGPT is trying to answer all my stated instructions in one go, thus within its first answer and to my understanding that context-window is limited to a certain amount of characters, perhaps its best that ChatGPT will split the instructions over the next chat-iteration within its chat session.

I hope this makes sense, could you assist me with advice for the:

  • Instructions and how should I write these, e.g. markdown
  • Creating a Template, split Processing?
  • Which format should I use to upload the transcript?
  • Should I add knowledge files in regards to the GPTs mission?
  • Other advice, yes please.
round fulcrumBOT
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Hi @placid canyon. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:

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Based on the information provided in the knowledge sources, here are some suggestions that might help you optimize your custom GPT for in-depth summarization of video transcripts:

  1. Instructions: The instructions you provide to your GPT play a crucial role in determining the output. You should be as specific as possible about what you want the GPT to do. For example, if you want the GPT to provide key points, important takeaways, and standout quotes, you should explicitly state this in your instructions. You can also specify the format you want the summary in, such as bullet points or paragraphs. However, the knowledge sources do not provide specific information on whether markdown can be used in instructions.

  2. Creating a Template, Split Processing: The knowledge sources do not provide specific information on creating a template or split processing for custom GPTs. However, it's worth noting that GPTs are designed to generate responses based on the input they receive. If you want the GPT to process the instructions in a certain way, you might need to experiment with different ways of structuring your instructions.

  3. Transcript Format: The knowledge sources suggest that .txt format is generally a good choice for uploading files to a custom GPT. One user reported success after re-uploading a file as a .txt instead of .md and waiting for the file to be indexed (source (https://community.openai.com/t/654419)).

  4. Adding Knowledge Files: You can add extra knowledge to your custom GPT by uploading documents. This could potentially help the GPT better understand the context of the video transcripts and generate more in-depth summaries (source (https://community.openai.com/t/499008)).

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  1. Other Advice: It's important to remember that training a GPT on a large dataset requires significant computational resources. You should consider strategies for managing these resources effectively. After training, you should evaluate the model’s performance in accurately reflecting the desired communication style. You can use various metrics or methods to assess the quality and reliability of the outputs (source (https://community.openai.com/t/595943)).

Please note that these are general suggestions based on the information available in the knowledge sources. You might need to experiment with different approaches to find what works best for your specific use case.

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:

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placid canyon
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@round fulcrum I'm working on customizing a GPT model to generate detailed summaries of video transcripts, focusing on extracting key takeaways, memorable quotes, and insightful themes. Given the constraints of character limits in instructions and the need for clarity and depth, could you provide a step-by-step guide or foundation-template for setting up my model to achieve this? Additionally, I would appreciate any best practices or recommendations for instruction design, data formatting, and leveraging features within the GPT-builder UI.

round fulcrumBOT
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Let me check the knowledge base for you. One moment! :books:

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Based on the information provided in the knowledge sources, here's a step-by-step guide to setting up your custom GPT model for generating detailed summaries of video transcripts:

  1. Create a GPT: Start by creating a new GPT at chat.openai.com/create (https://chat.openai.com/create). You can use the GPT Builder to help you build a new GPT by providing instructions like, "Make a GPT that generates detailed summaries of video transcripts" (source (https://help.openai.com/en/articles/8554397-creating-a-gpt)).

  2. Configure Your GPT: In the Configure tab, you can set the name and description of your GPT, and select the actions you would like your GPT to take. You can also provide detailed instructions or guidelines on how the GPT should behave, its functionalities, and any particular behaviors to avoid (source (https://help.openai.com/en/articles/8554397-creating-a-gpt#h_9fdf0ceaf0)).

  3. Design Your Instructions: When designing your instructions, be as specific as possible about what you want the GPT to do. For example, you could instruct the GPT to "Extract key takeaways, memorable quotes, and insightful themes from the provided video transcript. Summarize these in a detailed and coherent manner." You can also specify the format you want the summary in, such as bullet points or paragraphs. If you want the GPT to process the instructions in a certain way, you might need to experiment with different ways of structuring your instructions (source (https://platform.openai.com/docs/guides/prompt-engineering)).

  4. Format Your Data: The knowledge sources suggest that .txt format is generally a good choice for uploading files to a custom GPT. You should ensure that your video transcripts are clean and organized for optimal training efficiency (source (https://community.openai.com/t/595943)).

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  1. Add Knowledge Files: You can add extra knowledge to your custom GPT by uploading documents. This could potentially help the GPT better understand the context of the video transcripts and generate more in-depth summaries (source (https://community.openai.com/t/499008)).

  2. Publish Your GPT: Once you're satisfied with your GPT, you can publish it and share it with other people if you'd like (source (https://help.openai.com/en/articles/8554397-creating-a-gpt)).

Remember, these are general suggestions based on the information available in the knowledge sources. You might need to experiment with different approaches to find what works best for your specific use case.

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon: