ColBERTFuture Data Systems
|
Jina RerankerJina
|
|||||
Related Products
|
||||||
About
ColBERT is a fast and accurate retrieval model, enabling scalable BERT-based search over large text collections in tens of milliseconds. It relies on fine-grained contextual late interaction: it encodes each passage into a matrix of token-level embeddings. At search time, it embeds every query into another matrix and efficiently finds passages that contextually match the query using scalable vector-similarity (MaxSim) operators. These rich interactions allow ColBERT to surpass the quality of single-vector representation models while scaling efficiently to large corpora. The toolkit includes components for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. ColBERT integrates with Pyserini for retrieval and provides integrated evaluation for multi-stage pipelines. It also includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts.
|
About
Jina Reranker v2 is a state-of-the-art reranker designed for Agentic Retrieval-Augmented Generation (RAG) systems. It enhances search relevance and RAG accuracy by reordering search results based on deeper semantic understanding. It supports over 100 languages, enabling multilingual retrieval regardless of the query language. It is optimized for function-calling and code search, making it ideal for applications requiring precise function signatures and code snippet retrieval. Jina Reranker v2 also excels in ranking structured data, such as tables, by understanding the downstream intent to query structured databases like MySQL or MongoDB. With a 6x speedup over its predecessor, it offers ultra-fast inference, processing documents in milliseconds. The model is available via Jina's Reranker API and can be integrated into existing applications using platforms like Langchain and LlamaIndex.
|
|||||
Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
|||||
Audience
Academic researchers and developers seeking a tool for implementing and evaluating listwise reranking with large language models
|
Audience
Developers and data scientists interested in a solution to enhance relevance and performance
|
|||||
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
|
Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
|
|||||
API
Offers API
Supported
|
API
Offers API
Supported
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
Free
Free Version
Supported
Free Trial
Not Supported
|
Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
|
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Supported
|
|||||
Company InformationFuture Data Systems
United States
github.com/stanford-futuredata/ColBERT
|
Company InformationJina
Founded: 2020
United States
jina.ai/reranker/
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
|
|||||
|
|
|
|||||
|
|
|
|||||
Categories |
Categories |
|||||
Integrations
Amazon Web Services (AWS)
Not Supported
Google Cloud Platform
Not Supported
LangChain
Not Supported
LlamaIndex
Not Supported
Microsoft Azure
Not Supported
MongoDB
Not Supported
MySQL
Not Supported
|
Integrations
Amazon Web Services (AWS)
Supported
Google Cloud Platform
Supported
LangChain
Supported
LlamaIndex
Supported
Microsoft Azure
Supported
MongoDB
Supported
MySQL
Supported
|
|||||
|
|
|