Coding / Research first

Explore Qwen2.5 Coder 7B Instruct locally

Qwen2.5 Coder 7B Instruct is an instruction-tuned, code-specific causal language model from the Qwen2.5-Coder series, released under the Apache 2.0 license in the Qwen/Qwen2.5-Coder-7B-Instruct repository. According to its official model card, the repository contains the instruction-tuned 7B variant with 7.61B parameters (6.53B non-embedding), 28 layers, GQA with 28 query and 4 KV attention heads, and a full context length of 131,072 tokens. The model card states improvements in code generation, code reasoning, and code fixing, as well as long-context support and general/mathematical capabilities. It is a causal language model built for text generation using Transformers, with safetensors and chat/code tags.

Not yet tested
This is a source-based starting point. We haven’t independently tested this workflow yet. Source-based estimates are separate from our test results. Measured speed and our verdict will appear after a reproducible test.

Before you begin

Difficulty
Research first
Time required
Not yet tested
Software
Check official model card
Hardware
Not yet tested
Required VRAM
Not yet tested
Dependencies
See official model card
Read the official model card

The workflow

1

Read the publisher’s model card

Check the linked model card for its current license, files, required software, and official examples. Follow its instructions for your operating system.

2

Check your hardware before downloading

Use the YouRunAI model page to screen memory needs. Treat estimates as a first pass; confirm the published requirements and available quantization files.

3

Try a small official example

Use an example from the official model card to investigate Code generation. Start with a small input and confirm output quality and memory use before expanding the task.

The model behind this workflow

Qwen2.5 Coder · 7B

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