Qwen2.5-Coder-3B-Instruct

Qwen2.5-Coder Series: A 3B parameter instruction-tuned model.

CommonProductProgrammingCode GenerationCode Reasoning

Qwen2.5-Coder is the latest series of the Qwen large language model, focused on code generation, reasoning, and repair. Based on the powerful Qwen2.5, this model series significantly enhances code generation, reasoning, and repair capabilities by increasing training tokens to 5.5 trillion, including source code, text grounding, synthetic data, and more. The Qwen2.5-Coder-3B model contains 3.09B parameters, 36 layers, 16 attention heads (Q), and 2 attention heads (KV), with a total context length of 32,768 tokens. It stands out among open-source code LLMs, matching the coding capabilities of GPT-4o, and provides developers with a powerful code assistance tool.

Code Generation: Significantly enhances code generation capabilities
helping developers quickly implement code logic.
Code Reasoning: Improves the model's understanding of code logic
increasing the accuracy of code reasoning.
Code Repair: Aids developers in identifying and fixing errors in code.
Full Parameter Coverage: Covers parameter scales from 0.5B to 32B to meet diverse developer needs.
Multilingual Support: Primarily supports English
suitable for international development teams.
High-Performance Architecture: Utilizes a transformers architecture
incorporating advanced technologies such as RoPE

The target audience for the Qwen2.5-Coder-3B-Instruct model is developers
particularly software engineers who seek intelligent assistance in programming tasks. This model can comprehend complex code logic and provide intelligent suggestions for code generation
reasoning
and debugging
thereby enhancing development efficiency and code quality. It serves as a powerful assistant for developers handling extensive codebases or working in multilingual environments.

Developers use the Qwen2.5-Coder-3B-Instruct model to quickly generate code for sorting algorithms.
During code debugging
the model assists developers in identifying and fixing potential bugs.
In collaborative settings
the model acts as a code review tool

1. Access the Hugging Face platform and locate the Qwen2.5-Coder-3B-Instruct model.
2. Import the necessary libraries and modules as provided in the code examples on the page.
3. Load the model and tokenizer using AutoModelForCausalLM and AutoTokenizer.
4. Prepare input prompts
such as writing a sorting algorithm.

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Monthly Visits

19075321

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45.07%

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5.5

Visit Duration

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Qwen2.5-Coder-3B-Instruct Visit Over Time

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