Codestral Embed

Codestral Embed

Mistral AI
StarCoder

StarCoder

BigCode
+
+

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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

StarCoder and StarCoderBase are Large Language Models for Code (Code LLMs) trained on permissively licensed data from GitHub, including from 80+ programming languages, Git commits, GitHub issues, and Jupyter notebooks. Similar to LLaMA, we trained a ~15B parameter model for 1 trillion tokens. We fine-tuned StarCoderBase model for 35B Python tokens, resulting in a new model that we call StarCoder. We found that StarCoderBase outperforms existing open Code LLMs on popular programming benchmarks and matches or surpasses closed models such as code-cushman-001 from OpenAI (the original Codex model that powered early versions of GitHub Copilot). With a context length of over 8,000 tokens, the StarCoder models can process more input than any other open LLM, enabling a wide range of interesting applications. For example, by prompting the StarCoder models with a series of dialogues, we enabled them to act as a technical assistant.

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

Developers interested in an LLM for code generation

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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Review this Software

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

BigCode
Founded: 2023
huggingface.co/blog/starcoder

Alternatives

Alternatives

CodeGemma

CodeGemma

Google
CodeQwen

CodeQwen

Alibaba
Voyage AI

Voyage AI

MongoDB
DeepSeek Coder

DeepSeek Coder

DeepSeek
voyage-4-large

voyage-4-large

Voyage AI
Tabby

Tabby

Tabby ML

Categories

Categories

Integrations

GitHub
ChatGPT
CodeQwen
Git
LM Studio
Mistral AI
Mistral Code
OpenAI
Python
Tabby
Taylor AI
Visual Studio Code

Integrations

GitHub
ChatGPT
CodeQwen
Git
LM Studio
Mistral AI
Mistral Code
OpenAI
Python
Tabby
Taylor AI
Visual Studio Code
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