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Fine-Tuning LLaMA for Multi-Stage Text Retrieval

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Manage episode 427553455 series 3474385
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/fine-tuning-llama-for-multi-stage-text-retrieval.
Discover how fine-tuning LLaMA models enhances text retrieval efficiency and accuracy
Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #llama, #llm-fine-tuning, #fine-tuning-llama, #multi-stage-text-retrieval, #rankllama, #bi-encoder-architecture, #transformer-architecture, #hackernoon-top-story, and more.
This story was written by: @textmodels. Learn more about this writer by checking @textmodels's about page, and for more stories, please visit hackernoon.com.
This study explores enhancing text retrieval using state-of-the-art LLaMA models. Fine-tuned as RepLLaMA and RankLLaMA, these models achieve superior effectiveness for both passage and document retrieval, leveraging their ability to handle longer contexts and exhibiting strong zero-shot performance.

  continue reading

269 episodes

Artwork
iconShare
 
Manage episode 427553455 series 3474385
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/fine-tuning-llama-for-multi-stage-text-retrieval.
Discover how fine-tuning LLaMA models enhances text retrieval efficiency and accuracy
Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #llama, #llm-fine-tuning, #fine-tuning-llama, #multi-stage-text-retrieval, #rankllama, #bi-encoder-architecture, #transformer-architecture, #hackernoon-top-story, and more.
This story was written by: @textmodels. Learn more about this writer by checking @textmodels's about page, and for more stories, please visit hackernoon.com.
This study explores enhancing text retrieval using state-of-the-art LLaMA models. Fine-tuned as RepLLaMA and RankLLaMA, these models achieve superior effectiveness for both passage and document retrieval, leveraging their ability to handle longer contexts and exhibiting strong zero-shot performance.

  continue reading

269 episodes

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