I'm working on a restaurant similarity search engine and leveraging semantic search to deliver more accurate results. I was curious to see how different embedding models would perform on this task. You can find the notebook with the code and the results here
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Magellol/benchmarking-embedding-models
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Explore how to benchmark embedding models to optimize restaurant discovery using semantic search
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