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Solution Accelerator

Enhancing Product Search With Large Language Models (LLMs)

Pre-built code, sample data and step-by-step instructions ready to go in a Databricks Notebook

Enhancing Product Search with Large Language Models

Helping customers find the products they need

When customers can’t easily find what they’re looking for, they’re more likely to become frustrated and switch to competitors, leading to lost sales. Through the use of text generation capabilities of large language models (LLMs), retailers can analyze product descriptions and user prompts to provide relevant results — increasing customer satisfaction and the likelihood of successful purchases.

With this Solution Accelerator, organizations can:

  • Unify product, query and label data within a retailer’s product catalog
  • Enable rapid search with analytics against numerical arrays
  • Train and deploy an LLM model with Databricks Model Serving
Download notebook

Resources

Automating product review summarization with Large Language Models (LLMs)

Blog

Enhancing Product Search With Large Language Models (LLMs)

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Retail in the Age of Generative AI

Blog

Retail in the Age of Generative AI

10 ways large language models (LLMs) may impact the retail industry

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Fine-Tuning Large Language Models with Hugging Face and DeepSpeed

Blog

Fine-Tuning Large Language Models With Hugging Face and DeepSpeed

Easily apply and customize large language models of billions of parameters

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