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Fine-Tuning Cohere's Reranker

Blog post from Weaviate

Post Details
Company
Date Published
Author
Erika Cardenas
Word Count
3,599
Company Posts That Month
5
Language
English
Hacker News Points
-
Post removed?
No
Summary

Weaviate, a vector database, introduced reranking at the second stage in version 1.20. This feature allows users to improve search relevance by adding reranking to the second-stage of their search process. Cohere's rerank endpoint enables users to build search systems that add reranking at the last stage, and fine-tuning boosts the model's performance in unique domains. The blog post demonstrates how to fine-tune Cohere's reranker model using Weaviate's blogs dataset and DSPy's signature and chain-of-thought module. It also explains how to re-index data with a new schema that includes the fine-tuned model ID, and how to query the database with and without reranking.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
LLM 8 2,401 292 122 -7%
AI Model Fine-tuning 4 474 91 59 +12%
Vector Search 4 2,087 216 81 +23%
RAG 2 1,125 154 56 -17%
Real-time 2 2,379 618 172 -8%
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