Mistral AI Unveils Mistral 7B, An Open-Source LLM with 7.3B Parameters

Mistral AI announces the release of Mistral 7B, an open-source language model with 7.3 billion parameters. French artificial intelligence firm Mistral AI recently raised a sizable seed investment. With its first major language model (LLM), Mistral 7B, the business set out with a goal to transform generative artificial intelligence (AI). Furthermore, the business supports a community-driven development strategy in an effort to compete with huge proprietary AI solutions. Along with its enormous stature, it is causing a stir due to its outstanding powers, which surpass those of its larger competitors. The model is completely free to use and claims to outperform others of its size.

A startup on the rise

Alumni from Google’s DeepMind and Meta formed Mistral AI, a firm with headquarters in Paris. The business made its debut earlier this year with an unprecedented $118 million seed investment round and its recognizable Word Art logo. Mistral AI was thrust into the spotlight by this funding, the largest seed round in European history. Its goal is simple: to make AI useful for businesses by utilizing contributions from customers and publicly available data. The business has begun the process of achieving this goal with the launch of Mistral 7B.

Mistral Open models for AI are designed to provide better adaptability, enabling adaptation to particular tasks and user needs. This strategy is promoted as useful for companies looking to retain performance while keeping expenses down. The business also thinks open-source models will be essential weapons in the fight against AI’s ethical problems. They consist of bias and censorship. The capacity to audit generative models for errors and abuse is becoming more and more important as they continue to have an impact on society.

Mistral 7B can be a game-changer

Mistral 7B is not a typical LLM. It surpasses larger versions like Meta’s Llama 2 13B with its modest 7.3 billion parameters, creating a new benchmark for power and efficiency. In addition to being excellent at English language tests, this model also exhibits exceptional coding skills. This adaptability makes a variety of enterprise-focused applications possible. Mistral 7B is remarkable for being open-source and distributed under the Apache 2.0 license. This indicates that there are no restrictions on who can customize and use the setting. It may consist of enterprise scenarios and local or cloud-based apps.

Mistral AI thinks that a community-driven, open-source strategy can outperform the black-box methods that others have established as the industry norm. Mistral proposes that community-backed solutions are the way of the future by drawing parallels with the open-source revolutions in operating systems and web browsers. With the release of Mistral 7B, the company has taken its first big step toward developing specialized models that can compete with more substantial and well-established AI solutions. Mistral 7B is an improvement over other tiny LLM, such as 2. At far lower computing costs, it provides comparable capabilities.

How to Use Mistral 7B for Free

Hugging Face and GitHub both offer the Mistral 7B model for download along with documentation. Users can also communicate with the Mistral 7B Instruct Model using the Perplexity labs. Additionally, the business launched a Discord channel for teamwork and problem-solving.

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RELEASE ab979f50d7d406ab8d0b07d09806c72c

— Mistral AI (@MistralAI) September 27, 2023

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Benchmarks are more powerful than words

Despite only recently entering the market, Mistral 7B has already established its worth in benchmark tests. The model frequently outperforms open-source competition in head-to-head comparisons. It easily defeats Llama 2 7B and 13B, displaying its versatility. One of Mistral 7B’s primary advantages is the use of Grouped Query Attention (GQA) for extremely quick inference. Additionally, Sliding Window Attention (SQA) is used to manage longer sequences with minimal computing overhead. Its performance is improved across the board thanks to this novel method.

Improving cost-performance ratios

The cost-effectiveness of the Mistral 7B’s performance is an attractive feature. We can appreciate the memory savings and throughput improvements offered by computing “equivalent model sizes” by doing so. Mistral 7B performs as well in reasoning, comprehension, and STEM thinking as a Llama 2 model that is more than three times as big.

The Future of open-source AI

A potentially strong and open-source rival to current LLM like Mistral 7B that offers more customization options and more control over data security may present new chances for enterprises to use AI. The movement to open-source generative models mark a critical turning point in the AI sector, challenging established proprietary models on moral and technical grounds.

Among language AI models, Mistral 7B marks a notable advancement. It has the potential to revolutionize how businesses use artificial intelligence for a variety of applications thanks to its small size, open-source nature, and exceptional performance. We may expect even further advancements in artificial intelligence as Mistral AI keeps on innovating.

Here’s what they said

The company said in the blog post, 

We’re committing to release the strongest open models in parallel to developing our commercial offering. We will propose optimised proprietary models for on-premise/virtual private cloud deployment. These models will be distributed as white-box solutions, making both weights and code sources available. We are actively working on hosted solutions and dedicated deployment for enterprises.

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