Qwen2.5-Coder-7B-Instruct-GPTQ-Int4 is a quantized 7B parameter model hosted on Hugging Face. It belongs to the class of instruction-tuned large language models specialized for coding tasks.
The model includes a specific chat template that defines its behavior for conversations. When the first message is a system prompt it uses that content; otherwise it defaults to the instruction that it is Qwen created by Alibaba Cloud and a helpful assistant. The template further supports tool calling by providing function signatures inside XML tags and instructing the model to return calls in a structured JSON format wrapped in tool_call tags. This enables the model to invoke external functions during interaction.
It is delivered as a downloadable model repository on the Hugging Face platform. The GPTQ-Int4 designation indicates the model has been quantized to 4-bit integer precision using the GPTQ method, allowing it to run with reduced memory requirements compared to the full-precision version. The page provides the exact prompt format used by the model for consistent behavior across deployments.
No pricing information appears because the artifact is freely downloadable.
In the Coding AI & assistants space, Qwen2.5 Coder 7B Instruct takes a focused approach. It focuses on accessing and running a high-performance open code LLM locally or via API without needing massive GPU resources. It is built as an open-source project for developers. Qwen2.5 Coder 7B Instruct is open source under the Open Source license. Qwen2.5 Coder 7B Instruct is available on the web, the command line, and API, and it can be self-hosted.
It is developed by Alibaba Cloud (China), and it first shipped in 2024. Development happens publicly on GitHub with 16.7k stars. It competes in a saturated segment with 25 similar projects in PulseGate's index. Key capabilities include Code Generation, Instruction Following, and Tool Calling. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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