Mistral 7B Instruct v0.3 is an instruction fine-tuned version of the Mistral 7B v0.3 language model. It features an extended vocabulary of 32,768 tokens, supports the v3 tokenizer, and includes function calling capabilities. Optimized for instruction-following tasks, it excels in generating responses for chat applications, code generation, and understanding structured prompts. The model is designed to work efficiently with the Mistral inference library, enabling developers to deploy it across various natural language processing applications.
Fine-tuningDocs | Mistral 7B Instruct v0.3 can be customized with your data to improve responses. Fireworks uses LoRA to efficiently train and deploy your personalized model |
On-demand DeploymentDocs | On-demand deployments allow you to use Mistral 7B Instruct v0.3 on dedicated GPUs with Fireworks' high-performance serving stack with high reliability and no rate limits. |
Mistral 7B Instruct v0.3 is an instruction-tuned version of the Mistral 7B v0.3 base model, developed by Mistral AI. It supports the v3 tokenizer, includes function calling capabilities, and is optimized for instruction-following tasks like chat, code generation, and structured prompt handling.
This model is designed for:
The model supports a context length of 32,768 tokens.
The full 32.8K token window is supported on Fireworks on-demand deployments.
Users are expected to set decoding parameters manually (e.g., temperature, top_p) via API or CLI.
transformers v4.42.0+) for function calling compatibilityThe model has 7.2 billion parameters.
Yes. Fireworks supports LoRA-based fine-tuning for this model on dedicated infrastructure.
Token usage is measured by the total of input and output tokens.
The model is released under the Apache 2.0 license, which permits unrestricted commercial use.