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@@ -36,5 +36,7 @@ There are many opportunities to effectively scale this body of work.
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- Using our [fine tuned model](https://huggingface.co/tykiww/llama3-8b-meetingQA) trained both on the alpaca dataset and a *noisy* synthetic dataset of over 3000 product, technical, and academic meetings.
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- Updating our RAG retrieval methods: query more than meetings, change similarity search, embeddings, receive added context, account for the freshness of information, etc.
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This demo is just a peek. More to come!
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- Using our [fine tuned model](https://huggingface.co/tykiww/llama3-8b-meetingQA) trained both on the alpaca dataset and a *noisy* synthetic dataset of over 3000 product, technical, and academic meetings.
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- Updating our RAG retrieval methods: query more than meetings, change similarity search, embeddings, receive added context, account for the freshness of information, etc.
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note: There is an Out-of-memory issue with handling larger text. Currently working on chunking out batches on better sentiment groups prior to submitting data into the pipeline.
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This demo is just a peek. More to come!
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