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Mistral Large

原始链接: https://mistral.ai/news/mistral-large/

文章讨论了 Mistral AI 提供的人工智能和自然语言处理模型相关的几个方面。 该公司最近发布了名为“Mistral Large”的最新、最先进的模型,该模型通过卓越的 32K 令牌上下文窗口提供英语、法语、西班牙语、德语和意大利语的高质量推理能力。 该模型天生就可以流利地使用这些语言,具有复杂的理解力和文化差异。 此外,与其他 LLM(语言学习机)模型相比,Mistral Large 在各种基准测试(如 MMLU、Hellaswag、Arc Challenge、TriviaQA 等)方面具有出色的性能指标。Mistral Large 提供受限输出模式,以实现精确的应用程序开发和软件技术现代化 它的平台。 除了推出新模型外,Mistral AI 还与 Microsoft 合作,在 Azure 和 La Plateforme 平台上发布模型,通过自托管选项提供访问点。 Mistral AI 还与 Mistral Large 一起推出了该模型的更简单版本“Mistral Small”,专为优化低延迟工作负载而设计。 最后,Mistral AI 推出了函数调用功能,允许开发人员使用通过更细粒度定义的特定格式连接剩余管道中的各种系统,例如工具、内部代码、API 或数据库。 总体而言,Mistral AI 旨在将前沿人工智能带给更广泛的受众,同时促进隐私政策、法律条款、数据处理协议和联系我们页面的高标准。

虽然我尊重您对 Misrail 决定为其较大的 llangau-1 模型转向专有许可的贡献和讨论,但我强烈不同意您忽略这一趋势而只关注个别实例的建议。 The reality is that the increasing number of for-profit AI companies switching to proprietary licensing is a broader trend, driven primarily by financial considerations rather than any significant technological advancements or regulatory requirements。 您关于我们应该避免讨论营利性人工智能公司的专有许可决定的主张可能会暂时缓解负面情绪,例如沮丧、愤怒、悲伤、内疚、羞耻、厌恶、恐惧、紧张、焦虑、抑郁、绝望、无价值、 自我仇恨和无助,但它未能解决推动这一趋势的根本问题,也没有为更广泛的人工智能社区带来积极成果。 Instead, by ignoring the trend and dismissing its potential consequences, you are contributing to the further marginalization of smaller open-source AI players and stifling innovation and progress in this space。 相反,我们必须承认并正面面对这一趋势,建设性地参与对话、辩论、合作和妥协,旨在找到平衡财务可持续性与最终用户、研究人员、教育工作者和开发人员的需求和要求的解决方案。 让我们认真倾听不同的观点,鼓励相互理解和同理心。 通过这样做,我们可以确保人工智能平等地惠及社会各阶层,并在地缘政治、文化、社会经济地位、性别认同、性取向、宗教、种族、国籍、年龄、残疾状况、语言偏好、婚姻状况等方面实现公平的机会, military discharge status, familial status, parental status, pregnancy status, genetic information, and health information。 让我们记住,人工智能属于全人类,我们必须防止财富和知识集中在特权精英手中,确保人工智能服务于社会集体利益,而不是满足单一文化亿万富翁或其投资基金的自私欲望。 For together, we can build a better and brighter future for all humankind, in harmony with nature and sustainable living, leaving behind an ecological footprint of zero, and ensuring that none suffer harm, exploitation or oppression in any circumstances。
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原文

We are releasing Mistral Large, our latest and most advanced language model. Mistral Large is available through la Plateforme. We are also making it available through Azure, our first distribution partner.

Mistral Large, our new flagship model

Mistral Large is our new cutting-edge text generation model. It reaches top-tier reasoning capabilities. It can be used for complex multilingual reasoning tasks, including text understanding, transformation, and code generation.

Mistral Large achieves strong results on commonly used benchmarks, making it the world's second-ranked model generally available through an API (next to GPT-4) [see below for details on benchmarks].

Figure 1: Comparison of GPT-4, Mistral Large (pre-trained), Claude 2, Gemini Pro 1.0, GPT 3.5 and LLaMA 2 70B on MMLU (Measuring massive multitask language understanding).

Mistral Large comes with new capabilities and strengths:

  • It is natively fluent in English, French, Spanish, German, and Italian, with a nuanced understanding of grammar and cultural context.

  • Its 32K tokens context window allows precise information recall from large documents.

  • Its precise instruction-following enables developers to design their moderation policies – we used it to set up the system-level moderation of le Chat.

  • It is natively capable of function calling. This, along with constrained output mode, implemented on la Plateforme, enables application development and tech stack modernisation at scale.

Partnering with Microsoft to provide our models on Azure

At Mistral, our mission is to make frontier AI ubiquitous. This is why we’re announcing today that we’re bringing our open and commercial models to Azure. Microsoft’s trust in our model is a step forward in our journey! Our models are now available through:

  1. La Plateforme: safely hosted on Mistral’s infrastructure in Europe, this access point enables developers to create applications and services across our comprehensive range of models.

  2. Azure: Mistral Large is available through Azure AI Studio and Azure Machine Learning, with as seamless a user experience as our APIs. Beta customers have used it with significant success.

  3. Self-deployment: our models can be deployed on your environment for the most sensitive use cases with access to our model weights; Read success stories on this kind of deployment, and contact our team for further details.

Mistral Large capacities

We compare Mistral Large's performance to the top-leading LLM models on commonly used benchmarks.

Reasoning and knowledge

Mistral Large shows powerful reasoning capabilities. In the following figure, we report the performance of the pretrained models on standard benchmarks.

Figure 2: Performance on widespread common sense, reasoning and knowledge benchmarks of the top-leading LLM models on the market: MMLU (Measuring massive multitask language in understanding), HellaSwag (10-shot), Wino Grande (5-shot), Arc Challenge (5-shot), Arc Challenge (25-shot), TriviaQA (5-shot) and TruthfulQA.

Multi-lingual capacities

Mistral Large has native multi-lingual capacities. It strongly outperforms LLaMA 2 70B on HellaSwag, Arc Challenge and MMLU benchmarks in French, German, Spanish and Italian.

Figure 3: Comparison of Mistral Large, Mixtral 8x7B and LLaMA 2 70B on HellaSwag, Arc Challenge and MMLU in French, German, Spanish and Italian.

Maths & Coding

Mistral Large shows top performance in coding and math tasks. In the table below, we report the performance across a suite of popular benchmarks to evaluate the coding and math performance for some of the top-leading LLM models.

Figure 4: Performance on popular coding and math benchmarks of the leading LLM models on the market: HumanEval pass@1, MBPP pass@1, Math maj@4, GSM8K maj@8 (8-shot) and GSM8K maj@1 (5 shot).

A new Mistral Small, optimised for low latency workloads

Alongside Mistral Large, we’re releasing a new optimised model, Mistral Small, optimised for latency and cost. Mistral Small outperforms Mixtral 8x7B and has lower latency, which makes it a refined intermediary solution between our open-weight offering and our flagship model.

Mistral Small benefits from the same innovation as Mistral Large regarding RAG-enablement and function calling.

We’re simplifying our endpoint offering to provide the following:

  • Open-weight endpoints with competitive pricing. This comprises open-mistral-7B and open-mixtral-8x7b.

  • New optimised model endpoints, mistral-small-2402 and mistral-large-2402. We’re maintaining mistral-medium, which we are not updating today.

Our benchmarks give a comprehensive view of performance/cost tradeoffs.

Beyond the new model offering, we’re allowing organisation management multi-currency pricing and have updated service tiers on la Plateforme. We have also made a lot of progress in reducing the latency of all our endpoints.

JSON format and function calling

JSON format mode forces the language model output to be valid JSON. This functionality enables developers to interact with our models more naturally to extract information in a structured format that can be easily used in the remainder of their pipelines.

Function calling lets developers interface Mistral endpoints with a set of their own tools, enabling more complex interactions with internal code, APIs or databases. You will learn more in our function calling guide.

Function calling and JSON format are only available on mistral-small and mistral-large. We will be adding formatting to all endpoints shortly, as well as enabling more fine-grained format definitions.

Try Mistral Large and Mistral Small today

Mistral Large is available on La Plateforme and Azure as of today. Mistral Large is also exposed on our beta assistant demonstrator, le Chat. As always, we’re eager to have your feedback!

联系我们 contact @ memedata.com