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Qwen2.5 Coder 32B Instruct GPTQ Int8 by Qwen

 »  All LLMs  »  Qwen  »  Qwen2.5 Coder 32B Instruct GPTQ Int8   URL Share it on

  1816   
  Arxiv:2309.00071   Arxiv:2407.10671   Arxiv:2409.12186   8-bit   Autotrain compatible Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-coder-...   Chat   Code   Codegen   Codeqwen   Conversational   En   Endpoints compatible   Gptq   Instruct   Quantized   Qwen   Qwen-coder   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct-GPTQ-Int8 

Qwen2.5 Coder 32B Instruct GPTQ Int8 Benchmarks

HumanEvalA: 63.38
Python Eva: 83.2 vs 92 (so35)-9.6%
Java Eval: 73.69
Javascript: 76.05
CPP Eval: 81.95
PHP Eval: 73.59
Julia Eval: 58.15
D Eval: 26.98
Lua Eval: 46.04
R Eval: 52.73
Racket Eva: 61.54
Rust Eval: 68.53
Swift Eval: 58.12
LLME Score: 0.21722
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 32B Instruct GPTQ Int8 (Qwen/Qwen2.5-Coder-32B-Instruct-GPTQ-Int8)
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Qwen2.5 Coder 32B Instruct GPTQ Int8 Parameters and Internals

Model Type 
Causal Language Model
Use Cases 
Areas:
Research, Commercial applications
Applications:
Code generation, Code reasoning, Code fixing, Mathematics
Primary Use Cases:
Enhancing coding capabilities, Long-context handling
Supported Languages 
en (Full support)
Training Details 
Data Sources:
Source code, Text-code grounding, Synthetic data
Data Volume:
5.5 trillion tokens
Methodology:
Pretraining & Post-training
Context Length:
131072
Model Architecture:
transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
Input Output 
Accepted Modalities:
text
LLM NameQwen2.5 Coder 32B Instruct GPTQ Int8
Repository 🤗https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct-GPTQ-Int8 
Base Model(s)  Qwen/Qwen2.5-Coder-32B-Instruct   Qwen/Qwen2.5-Coder-32B-Instruct
Model Size32b
Required VRAM35.1 GB
Updated2025-09-24
MaintainerQwen
Model Typeqwen2
Instruction-BasedYes
Model Files  3.9 GB: 1-of-9   4.0 GB: 2-of-9   4.0 GB: 3-of-9   4.0 GB: 4-of-9   4.0 GB: 5-of-9   4.0 GB: 6-of-9   4.0 GB: 7-of-9   4.0 GB: 8-of-9   3.2 GB: 9-of-9
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.43.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2.5-Coder-32B-Instruct-GPTQ-Int8.

Rank the Qwen2.5 Coder 32B Instruct GPTQ Int8 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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Release v20241124
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