Mistral-Large-Instruct-2407-GGUF

💫 Community Model> Mistral Large Instruct 2407 by Mistralai

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Model creator: mistralai<br> Original model: Mistral-Large-Instruct-2407<br> GGUF quantization: provided by bartowski based on llama.cpp release b3441<br>

Model Summary:

Mistral Large 2 has a 128k context window and supports dozens of languages including French, German, Spanish, Italian, Portuguese, Arabic, Hindi, Russian, Chinese, Japanese, and Korean, along with 80+ coding languages including Python, Java, C, C++, JavaScript, and Bash.

Prompt Template:

Choose the Mistral Instruct preset in your LM Studio. Under the hood, the model will see a prompt that's formatted like so:

<s>[INST] {prompt}[/INST] </s>

Technical Details

Mistral Large 2 features enhanced instruction-following and conversational capabilities. Additionally, a significant effort was also devoted to enhancing the model’s reasoning capabilities and decreasing the model’s tendency to “hallucinate” or generate plausible-sounding but factually incorrect or irrelevant information. This was achieved by fine-tuning the model to be more cautious and discerning in its responses, ensuring that it provides reliable and accurate outputs.

Mistral Large 2 is equipped with enhanced function calling and retrieval skills and has undergone training to proficiently execute both parallel and sequential function calls, enabling it to serve as the power engine of complex business applications.

Mistral Large 2 was trained on a large proportion of multilingual data. In particular, it excels in English, French, German, Spanish, Italian, Portuguese, Dutch, Russian, Chinese, Japanese, Korean, Arabic, and Hindi. Below are the performance results of Mistral Large 2 on the multilingual MMLU benchmark, compared to the previous Mistral Large, Llama 3.1 models, and to Cohere’s Command R+.

Special thanks

🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible.

🙏 Special thanks to Kalomaze for his dataset (linked here) that was used for calculating the imatrix for the IQ1_M and IQ2_XS quants, which makes them usable even at their tiny size!

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