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Mistral (7B) InstructInstruct Precisely

Try Mistral (7B) InstructAPI Documentation

Deploy Mistral 7B Instruct

32k Context

Handle Long Sequences

Process extended conversations and documents with full attention mechanism.

Fast Inference

Grouped-Query Attention

Achieve high-speed generation via GQA for efficient API calls.

Instruction Tuned

Follow Complex Tasks

Execute instructions, code gen, and dialogues from Mistral (7B) Instruct model.

Examples

See what Mistral (7B) Instruct can create

Copy any prompt below and try it yourself in the playground.

Code Snippet

“Write a Python function to sort a list of dictionaries by a key value, handling missing keys gracefully. Include type hints and docstring.”

Data Summary

“Summarize this sales report: [insert long report text]. Highlight top products, revenue trends, and recommendations in bullet points.”

Tech Explanation

“Explain transformer attention mechanisms step-by-step for beginners, using simple analogies and no math.”

Task Automation

“Generate a bash script to backup directories older than 30 days to S3, with logging and error handling.”

For Developers

A few lines of code.
Instruct. One API call.

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

  • Serverless: scales to zero, scales to millions
  • Pay per token, no minimums
  • Python and JavaScript SDKs, plus REST API
API Documentation 
import requests


response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

FAQ

Common questions about Mistral (7B) Instruct

Read the docs

Mistral (7B) Instruct is a 7B parameter LLM fine-tuned for instructions from Mistral AI base model. It excels in dialogue and task completion. Supports 32k context window.

Send POST requests to chat completions endpoint with model 'mistral-7b-instruct'. Use system and user messages for structured responses. Handles function calling.

Mistral (7B) Instruct LLM offers 32k tokens context. Enables long document summarization and multi-turn chats. Uses RoPE for extended sequences.

Generates at 182 tokens/second via grouped-query attention. Optimized for low-latency inference. Suitable for real-time apps.

Base model generates general text; Instruct version follows instructions for conversations. Instruct outperforms on MT-Bench among 7B models.

No built-in moderation mechanisms. Fine-tune for guardrails if needed. Apache 2.0 licensed for custom adaptations.

Ready to create?

Start generating with Mistral (7B) Instruct on ModelsLab.

Try Mistral (7B) InstructAPI Documentation