LexVecAlexandre Salle
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Pinecone Rerank v0Pinecone
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Related Products
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About
LexVec is a word embedding model that achieves state-of-the-art results in multiple natural language processing tasks by factorizing the Positive Pointwise Mutual Information (PPMI) matrix using stochastic gradient descent. This approach assigns heavier penalties for errors on frequent co-occurrences while accounting for negative co-occurrences. Pre-trained vectors are available, including a common crawl dataset with 58 billion tokens and 2 million words in 300 dimensions, and an English Wikipedia 2015 + NewsCrawl dataset with 7 billion tokens and 368,999 words in 300 dimensions. Evaluations demonstrate that LexVec matches or outperforms other models like word2vec in terms of word similarity and analogy tasks. The implementation is open source under the MIT License and is available on GitHub.
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About
Pinecone Rerank V0 is a cross-encoder model optimized for precision in reranking tasks, enhancing enterprise search and retrieval-augmented generation (RAG) systems. It processes queries and documents together to capture fine-grained relevance, assigning a relevance score from 0 to 1 for each query-document pair. The model's maximum context length is set to 512 tokens to preserve ranking quality. Evaluations on the BEIR benchmark demonstrated that Pinecone Rerank V0 achieved the highest average NDCG@10, outperforming other models on 6 out of 12 datasets. For instance, it showed up to a 60% boost on the Fever dataset compared to Google Semantic Ranker and over 40% on the Climate-Fever dataset relative to cohere-v3-multilingual or voyageai-rerank-2. The model is accessible through Pinecone Inference and is available to all users in public preview.
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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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
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Audience
Computational linguists and NLP researchers searching for a tool to improve their semantic analysis and language modeling
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Audience
AI developers looking for a tool to enhance the relevance and accuracy of search results in enterprise applications, particularly those leveraging RAG systems
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Pricing
$25 per month
Free Version
Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Supported
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Company InformationAlexandre Salle
Brazil
github.com/alexandres/lexvec
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Company InformationPinecone
Founded: 2019
United States
www.pinecone.io/blog/pinecone-rerank-v0-announcement/
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Categories |
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Integrations
Amazon Bedrock
Not Supported
Amazon SageMaker
Not Supported
Amazon Web Services (AWS)
Not Supported
Anyscale
Not Supported
Datavolo
Not Supported
Estuary Flow
Not Supported
Flowise
Not Supported
Gathr.ai
Not Supported
Google Cloud Platform
Not Supported
HoneyHive
Not Supported
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Integrations
Amazon Bedrock
Supported
Amazon SageMaker
Supported
Amazon Web Services (AWS)
Supported
Anyscale
Supported
Datavolo
Supported
Estuary Flow
Supported
Flowise
Supported
Gathr.ai
Supported
Google Cloud Platform
Supported
HoneyHive
Supported
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