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CodeQwen1.5 7B by Qwen

 »  All LLMs  »  Qwen  »  CodeQwen1.5 7B   URL Share it on

  2268   
  Arxiv:2309.16609   Autotrain compatible   En   Endpoints compatible   Pretrained   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Qwen/CodeQwen1.5-7B 

CodeQwen1.5 7B Benchmarks

HumanEvalA: 40.47
Python Eva: 50.79 vs 92 (so35)-44.8%
Java Eval: 42.15
Javascript: 50.07
CPP Eval: 48.35
PHP Eval: 50.92
Julia Eval: 37.27
D Eval: 16.03
Lua Eval: 46.29
R Eval: 27.95
Racket Eva: 24.89
Rust Eval: 47.56
Swift Eval: 43.33
LLME Score: 0.2181
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CodeQwen1.5 7B (Qwen/CodeQwen1.5-7B)

CodeQwen1.5 7B Parameters and Internals

Model Type 
text-generation, code generation
Use Cases 
Applications:
code infilling, code generation, text-to-SQL, bug fix
Considerations:
Be careful about stopping criteria.
Additional Notes 
Supporting 92 coding languages. Strong code generation capabilities and competitive performance across a series of benchmarks.
Training Details 
Data Volume:
3 trillion tokens
Methodology:
Group Query Attention (GQA) for efficient inference
Context Length:
64000
Model Architecture:
Transformer-based decoder-only language model
LLM NameCodeQwen1.5 7B
Repository 🤗https://huggingface.co/Qwen/CodeQwen1.5-7B 
Model Size7b
Required VRAM14.6 GB
Updated2025-02-22
MaintainerQwen
Model Typeqwen2
Model Files  3.9 GB: 1-of-4   4.0 GB: 2-of-4   4.0 GB: 3-of-4   2.7 GB: 4-of-4
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length65536
Model Max Length65536
Transformers Version4.39.3
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<fim_pad>
Vocabulary Size92416
Torch Data Typebfloat16

Quantized Models of the CodeQwen1.5 7B

Model
Likes
Downloads
VRAM
CodeQwen1.5 7B AWQ21555 GB
CodeQwen1.5 7B EXL2 8.0bpw177 GB

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Note: green Score (e.g. "73.2") means that the model is better than Qwen/CodeQwen1.5-7B.

Rank the CodeQwen1.5 7B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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 v20241227
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