Everyone Coder 33B V2 Base by rombodawg

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Everyone Coder 33B V2 Base Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Everyone Coder 33B V2 Base (rombodawg/Everyone-Coder-33b-v2-Base)

Everyone Coder 33B V2 Base Parameters and Internals

Model Type 
coding-specific
Additional Notes 
This Version 2 of the Everything-Coder-33b model uses the task_arithmetic merging method which significantly enhances coding performance. It addresses previous merging issues while maintaining model integrity.
Training Details 
Data Sources:
deepseek-ai/deepseek-coder-33b-instruct, codefuse-ai/CodeFuse-DeepSeek-33B, WizardLM/WizardCoder-33B-V1.1
Methodology:
fine-tuning and task_arithmetic merging
Input Output 
Input Format:
Alpaca prompt format
LLM NameEveryone Coder 33B V2 Base
Repository 🤗https://huggingface.co/rombodawg/Everyone-Coder-33b-v2-Base 
Model Size33b
Required VRAM66.5 GB
Updated2025-06-02
Maintainerrombodawg
Model Typellama
Model Files  9.7 GB: 1-of-7   9.8 GB: 2-of-7   9.8 GB: 3-of-7   9.8 GB: 4-of-7   9.9 GB: 5-of-7   9.9 GB: 6-of-7   7.6 GB: 7-of-7
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length16384
Model Max Length16384
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizerFast
Beginning of Sentence Token<|begin▁of▁sentence|>
End of Sentence Token<|end▁of▁sentence|>
Vocabulary Size32256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than rombodawg/Everyone-Coder-33b-v2-Base.

Rank the Everyone Coder 33B V2 Base 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 v20241227