LexVecAlexandre Salle
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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
No one wants their AI to respond with out-of-date information to a customer. Neum AI helps companies have accurate and up-to-date context in their AI applications. Use built-in connectors for data sources like Amazon S3 and Azure Blob Storage, vector stores like Pinecone and Weaviate to set up your data pipelines in minutes. Supercharge your data pipeline by transforming and embedding your data with built-in connectors for embedding models like OpenAI and Replicate, and serverless functions like Azure Functions and AWS Lambda. Leverage role-based access controls to make sure only the right people can access specific vectors. Bring your own embedding models, vector stores and sources. Ask us about how you can even run Neum AI in your own cloud.
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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
Developers searching for a platform to connect and sync data into vector stores for fast query and search
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Support
Phone Support
Not Supported
24/7 Live Support
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Online
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Support
Phone Support
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24/7 Live Support
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Online
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API
Offers API
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API
Offers API
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Pricing
Free
Free Version
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Free Trial
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Pricing
No information available.
Free Version
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Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
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Live Online
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In Person
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
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Company InformationAlexandre Salle
Brazil
github.com/alexandres/lexvec
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Company InformationNeum AI
www.neum.ai/
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Integrations
AWS Lambda
Not Supported
Amazon S3
Not Supported
Azure Blob Storage
Not Supported
Azure Functions
Not Supported
ChatGPT
Not Supported
GPT-3
Not Supported
GPT-3.5
Not Supported
GPT-4
Not Supported
OpenAI
Not Supported
Replicate
Not Supported
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Integrations
AWS Lambda
Supported
Amazon S3
Supported
Azure Blob Storage
Supported
Azure Functions
Supported
ChatGPT
Supported
GPT-3
Supported
GPT-3.5
Supported
GPT-4
Supported
OpenAI
Supported
Replicate
Supported
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