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Qwen2.5 Godzilla Coder 51B by DavidAU

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Qwen2.5 Godzilla Coder 51B is an open-source language model by DavidAU. Features: 32b LLM, VRAM: 102.1GB, Context: 32K, License: apache-2.0, Code Generating, LLM Explorer Score: 0.22.

  Autotrain compatible Base model:merge:open-r1/olymp... Base model:merge:qwen/qwen2.5-... Base model:open-r1/olympiccode... Base model:qwen/qwen2.5-coder-...   Chat   Code   Code generation   Codegen   Codeqwen   Coder   Coding   Conversational   En   Endpoints compatible   Merge   Moe   Qwen   Qwen-coder   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/DavidAU/Qwen2.5-Godzilla-Coder-51B 

Qwen2.5 Godzilla Coder 51B Benchmarks

LLME Score: 0.21769
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 Godzilla Coder 51B (DavidAU/Qwen2.5-Godzilla-Coder-51B)
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Qwen2.5 Godzilla Coder 51B Parameters and Internals

LLM NameQwen2.5 Godzilla Coder 51B
Repository 🤗https://huggingface.co/DavidAU/Qwen2.5-Godzilla-Coder-51B 
Base Model(s)  Qwen/Qwen2.5-Coder-32B   OlympicCoder 32B   Qwen/Qwen2.5-Coder-32B   open-r1/OlympicCoder-32B
Model Size32b
Required VRAM102.1 GB
Updated2025-09-23
MaintainerDavidAU
Model Typeqwen2
Model Files  5.0 GB: 1-of-21   4.9 GB: 2-of-21   5.0 GB: 3-of-21   4.8 GB: 4-of-21   4.9 GB: 5-of-21   5.0 GB: 6-of-21   4.9 GB: 7-of-21   4.8 GB: 8-of-21   4.9 GB: 9-of-21   5.0 GB: 10-of-21   4.8 GB: 11-of-21   5.0 GB: 12-of-21   4.8 GB: 13-of-21   5.0 GB: 14-of-21   4.8 GB: 15-of-21   5.0 GB: 16-of-21   4.9 GB: 17-of-21   4.9 GB: 18-of-21   4.9 GB: 19-of-21   4.9 GB: 20-of-21   3.9 GB: 21-of-21
Supported Languagesen
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.52.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Rank the Qwen2.5 Godzilla Coder 51B 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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