Codestral Embed

Codestral Embed

Mistral AI
Gensim

Gensim

Radim Řehůřek
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+

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About

Codestral Embed is Mistral AI's first embedding model, specialized for code, optimized for high-performance code retrieval and semantic understanding. It significantly outperforms leading code embedders in the market today, such as Voyage Code 3, Cohere Embed v4.0, and OpenAI’s large embedding model. Codestral Embed can output embeddings with different dimensions and precisions; for instance, with a dimension of 256 and int8 precision, it still performs better than any model from competitors. The dimensions of the embeddings are ordered by relevance, allowing users to choose the first n dimensions for a smooth trade-off between quality and cost. It excels in retrieval use cases on real-world code data, particularly in benchmarks like SWE-Bench, which is based on real-world GitHub issues and corresponding fixes, and Text2Code (GitHub), relevant for providing context for code completion or editing.

About

Gensim is a free, open source Python library designed for unsupervised topic modeling and natural language processing, focusing on large-scale semantic modeling. It enables the training of models like Word2Vec, FastText, Latent Semantic Analysis (LSA), and Latent Dirichlet Allocation (LDA), facilitating the representation of documents as semantic vectors and the discovery of semantically related documents. Gensim is optimized for performance with highly efficient implementations in Python and Cython, allowing it to process arbitrarily large corpora using data streaming and incremental algorithms without loading the entire dataset into RAM. It is platform-independent, running on Linux, Windows, and macOS, and is licensed under the GNU LGPL, promoting both personal and commercial use. The library is widely adopted, with thousands of companies utilizing it daily, over 2,600 academic citations, and more than 1 million downloads per week.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Enterprise software teams needing a tool for semantic code search, retrieval-augmented generation, and code analytics across large-scale codebases

Audience

Machine learning practitioners seeking a solution for topic modeling and semantic analysis of large text corpora

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Mistral AI
Founded: 2023
United States
mistral.ai/news/codestral-embed

Company Information

Radim Řehůřek
Founded: 2009
Czech Republic
radimrehurek.com/gensim/

Alternatives

Alternatives

GloVe

GloVe

Stanford NLP
word2vec

word2vec

Google
Voyage AI

Voyage AI

MongoDB
voyage-4-large

voyage-4-large

Voyage AI

Categories

Categories

Integrations

C
Cython
GitHub
Mistral AI
Mistral Code
NumPy
Python
fastText
word2vec

Integrations

C
Cython
GitHub
Mistral AI
Mistral Code
NumPy
Python
fastText
word2vec
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