Qwen2.5-Coder-3B-Instruct-GPTQ-Int4
3B parameter instruction tuning model in Qwen2.5-Coder series
Product Details
Qwen2.5-Coder is the latest series of Qwen large-scale language models, designed for code generation, reasoning and repair. The model is based on Qwen2.5 and extends the training tokens to 5.5 trillion, including source code, text code base, synthetic data, etc. Qwen2.5-Coder-32B is currently the leader in open source code LLM, and its coding capabilities match GPT-4o. This model is a GPTQ-quantized 4-bit instruction-tuned 3B parameter Qwen2.5-Coder model, which has the characteristics of causal language model, pre-training and post-training stages, transformers architecture, etc.
Main Features
How to Use
Target Users
The target audience is software developers, programming enthusiasts, and researchers who need to generate, reason, and repair code. The Qwen2.5-Coder series models can significantly improve programming efficiency, reduce development time, and help solve complex programming problems. They are a powerful assistant for developers and researchers.
Examples
Developers use Qwen2.5-Coder to generate the code for the sorting algorithm.
Researchers use models to perform logical reasoning and analysis on specific pieces of code.
Software engineers use models to fix errors in existing code and improve code stability.
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