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Using k-Means on the embeddings of 500 chunks of a book, i find the summary of top 20 densest chunks.

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Text-Summarization

I wanted to read the seminal book AI: A Modern Approach. So, i took the book, split it into chunks of manegable context length. Converted it to embeddings. Plotted them out. Clustered the top 20 with k means. Took the text and got the summary of top 20 groups. I used an LM Studio run on an RTX 3060. If you use LM Studio, you may be able to use this code by changing the book name in the code itself. I hope this helps. Questions are welcome. Ill try respponding gracefully and humbly.

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Using k-Means on the embeddings of 500 chunks of a book, i find the summary of top 20 densest chunks.

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