Understanding the Mistral-nemo-instruct-2407 model

Model overview

Model name

mistral-nemo-instruct-2407:fp8

Compatible Instance

• H100 (FP8)

Model introduction

Mistral Nemo is a state-of-the-art transformer model of 12B parameters, built by Mistral in collaboration with NVIDIA. This model is open-weight and distributed under the Apache 2.0 license. It was trained on a large proportion of multilingual and code data.

Why is it useful?

• Mistral Nemo offers a very large context window of up to 128k tokens, particularly useful for RAG applications.
• It is easy to use and a drop-in replacement in any system already using Mistral 7B.
• This model was designed for global, multilingual applications. It is particularly strong in English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and Hindi.

How to use it

Sending Inference requests

To perform inference tasks with your Mistral model deployed at Scaleway, use the following command:

curl -s \
-H "Authorization: Bearer <IAM API key>" \
-H "Content-Type: application/json" \
--request POST \
--url "https://<Deployment UUID>.ifr.fr-par.scw.cloud/v1/chat/completions" \
--data '{"model":"mistral-nemo-instruct-2407", "messages":[{"role": "user","content": "Sing me a song about Xavier Niel"}], "top_p": 1, "temperature": 0.35, "stream": false}'

Make sure to replace <IAM API key> and <Deployment UUID> with your actual IAM API key and the Deployment UUID you are targeting.

Receiving Managed Inference responses

Upon sending the HTTP request to the public or private endpoints exposed by the server, you will receive inference responses from the managed Managed Inference server. Process the output data according to your application’s needs. The response will contain the output generated by the LLM model based on the input provided in the request.