Qwen2.5 7B Instruct
A 7-billion-parameter language model from Alibaba, optimized for precise instruction following and handling long texts.
Overview
Qwen2.5 7B Instruct
Description of the Qwen2.5 7B Instruct neural network
Qwen2.5 7B Instruct is an open-source language model developed by Alibaba. It has 7.6 billion parameters and is specially tuned to accurately follow user instructions. The model can process texts longer than 8,000 tokens, analyze structured data, and return results in machine-readable formats, such as JSON. Compared to the previous version, Qwen2 7B Instruct, the new model demonstrates noticeably improved performance in mathematics and programming, and also supports more than 29 languages — from Chinese and English to French and Spanish.
Characteristics of Qwen2.5 7B Instruct
| Characteristic | Value |
|---|---|
| Number of parameters | 7.6 billion |
| Context window (max input tokens) | 131,100 tokens |
| Maximum output tokens | 8,200 tokens |
| Release date | September 19, 2024 |
| Training data volume | 18.0 trillion tokens |
| Average benchmark score | 65.6% |
| License | Apache 2.0 |
Who is the Qwen2.5 7B Instruct neural network suitable for?
Developers and machine learning engineers
The model suits those who build applications on top of large language models — from chatbots to tools for automatic code generation. The ability to fine-tune and Function Calling support make it convenient for integration into existing systems.
Researchers and data analysts
Specialists working with large volumes of text and structured data can use Qwen2.5 7B Instruct to extract information, analyze documents, and generate reports in JSON format.
Product teams working with multiple languages
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