Qwen2.5 Coder 0.5B Instruct by Qwen

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Qwen2.5 Coder 0.5B Instruct Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 Coder 0.5B Instruct (Qwen/Qwen2.5-Coder-0.5B-Instruct)

Qwen2.5 Coder 0.5B Instruct Parameters and Internals

Model Type 
Causal Language Models
Use Cases 
Areas:
research, commercial applications
Applications:
code generation, code reasoning, code fixing, Code Agents, mathematics
Supported Languages 
en (fluent)
Training Details 
Data Sources:
source code, text-code grounding, Synthetic data
Data Volume:
5.5 trillion tokens
Methodology:
Pretraining & Post-training
Context Length:
32768
Model Architecture:
transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias and tied word embeddings
Input Output 
Input Format:
structured prompt
Accepted Modalities:
text
Output Format:
generated text response
Release Notes 
Notes:
Significant improvements in code generation, reasoning, and fixing.
LLM NameQwen2.5 Coder 0.5B Instruct
Repository ๐Ÿค—https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct 
Base Model(s)  Qwen/Qwen2.5-Coder-0.5B   Qwen/Qwen2.5-Coder-0.5B
Model Size0.5b
Required VRAM1 GB
Updated2024-12-21
MaintainerQwen
Model Typeqwen2
Instruction-BasedYes
Model Files  1.0 GB
Supported Languagesen
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.43.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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Rank the Qwen2.5 Coder 0.5B Instruct Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217