voyage-code-3MongoDB
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Related Products
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About
Vectorize is a platform designed to transform unstructured data into optimized vector search indexes, facilitating retrieval-augmented generation pipelines. It enables users to import documents or connect to external knowledge management systems, allowing Vectorize to extract natural language suitable for LLMs. The platform evaluates multiple chunking and embedding strategies in parallel, providing recommendations or allowing users to choose their preferred methods. Once a vector configuration is selected, Vectorize deploys it into a real-time vector pipeline that automatically updates with any data changes, ensuring accurate search results. The platform offers connectors to various knowledge repositories, collaboration platforms, and CRMs, enabling seamless integration of data into generative AI applications. Additionally, Vectorize supports the creation and updating of vector indexes in preferred vector databases.
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About
Voyage AI introduces voyage-code-3, a next-generation embedding model optimized for code retrieval. It outperforms OpenAI-v3-large and CodeSage-large by an average of 13.80% and 16.81% on a suite of 32 code retrieval datasets, respectively. It supports embeddings of 2048, 1024, 512, and 256 dimensions and offers multiple embedding quantization options, including float (32-bit), int8 (8-bit signed integer), uint8 (8-bit unsigned integer), binary (bit-packed int8), and ubinary (bit-packed uint8). With a 32 K-token context length, it surpasses OpenAI's 8K and CodeSage Large's 1K context lengths. Voyage-code-3 employs Matryoshka learning to create embeddings with a nested family of various lengths within a single vector. This allows users to vectorize documents into a 2048-dimensional vector and later use shorter versions (e.g., 256, 512, or 1024 dimensions) without re-invoking the embedding model.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Organizations searching for a solution to improve their AI capabilities by optimizing their vector search indexes
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Audience
AI researchers and developers in search of a solution providing an embedding model for code retrieval
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
$0.57 per hour
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationVectorize
Founded: 2023
United States
vectorize.io
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Company InformationMongoDB
Founded: 2007
United States
blog.voyageai.com/2024/12/04/voyage-code-3/
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Categories |
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Integrations
Amazon S3
Azure Blob Storage
Confluence
Discord
Dropbox
Elasticsearch
Google Cloud Storage
Google Drive
Intercom
Milvus
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Integrations
Amazon S3
Azure Blob Storage
Confluence
Discord
Dropbox
Elasticsearch
Google Cloud Storage
Google Drive
Intercom
Milvus
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