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Mistral AI: Frontier AI in Your Hands

Mistral AI is at the forefront of pushing the boundaries of artificial intelligence. Their commitment to open models and community-driven innovation sets them apart. Discover Mistral 7B, their latest breakthrough in AI technology.

General
AuthorMistral AI
RepositoryGitHub
TypeLarge Language Model

Introduction

Mistral 7B v0.1 is Mistral AI's first Large Language Model (LLM). A Large Language Model (LLM) is an artificial intelligence algorithm trained on massive amounts of data that is able to generate coherent text and perform various natural language processing tasks.

The raw model weights are downloadable from the documentation and on GitHub.

A Docker image bundling vLLM, a fast Python inference server, with everything required to run our model is provided to quickly spin a completion API on any major cloud provider with NVIDIA GPUs.

Where to Start?

If you are interested in deploying the Mistral AI LLM on your infrastructure, check out the Quickstart. If you want to use the API served by a deployed instance, go to the Interacting with the model page or view the API specification.

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    SecureSpeak

    SecureSpeak

    SecureSpeak Enterprise emerges as a cutting-edge solution in the realm of secure digital communication, catering to the pressing need for privacy and data integrity in business interactions. At its foundation lies a sophisticated self-deployed language model, designed to scrutinize user inputs instantaneously, censoring any sensitive information with a blend of pre-configured rules and insights gleaned from historical data. This ensures that every piece of information is treated with the utmost confidentiality right from the start. SecureSpeak employs an innovative dual-storage system. This system archives both the original and the censored versions of inputs within SQL and vector databases, facilitating not only robust data management but also seamless retrieval and analysis. This strategic approach to data storage preserves the context and meaning of information, all while upholding stringent confidentiality standards. Central to SecureSpeak’s functionality is its use of Retrieval-Augmented Generation (RAG), powered by Vectara. This mechanism enriches the platform's responses with semantically related content from an extensive corporate database, alongside the capability to perform on-demand, context-specific queries. This not only enhances the relevance and accuracy of the responses but also ensures they remain within the bounds of privacy regulations. The SecureSpeak journey extends beyond immediate data processing to include the active refinement and application of collected insights. This process serves to enhance the overall user experience significantly, turning raw data into a strategic asset. Additionally, the system's language model is subject to ongoing fine-tuning, learning continuously from processed data to elevate its performance in censoring and generating responses. Through these meticulously designed features and processes, SecureSpeak Enterprise sets a new standard in secure, intelligent, and privacy-conscious digital communication.