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DareQwen 2.5 7B by Locutusque

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DareQwen 2.5 7B is an open-source language model by Locutusque. Features: 7b LLM, VRAM: 15.2GB, Context: 128K, Instruction-Based, Code Generating, Merged, LLM Explorer Score: 0.16.

  Merged Model   Arxiv:2306.01708   Arxiv:2311.03099   Ara   Autotrain compatible   Base model:qwen/qwen2.5-7b Base model:qwen/qwen2.5-7b-ins... Base model:qwen/qwen2.5-coder-... Base model:qwen/qwen2.5-math-7...   Codegen   Conversational   Deu   Endpoints compatible   Eng   Fra   Instruct   Ita   Jpn   Kor   Por   Qwen2   Region:us   Rus   Safetensors   Sharded   Spa   Tensorflow   Tha   Vie   Zho
Model Card on HF 🤗: https://huggingface.co/Locutusque/DareQwen-2.5-7B 

DareQwen 2.5 7B Benchmarks

LLME Score: 0.15656
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
DareQwen 2.5 7B (Locutusque/DareQwen-2.5-7B)
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DareQwen 2.5 7B Parameters and Internals

LLM NameDareQwen 2.5 7B
Repository 🤗https://huggingface.co/Locutusque/DareQwen-2.5-7B 
Base Model(s)  Qwen/Qwen2.5-Coder-7B-Instruct   Qwen/Qwen2.5-Math-7B-Instruct   Qwen/Qwen2.5-7B   Qwen/Qwen2.5-7B-Instruct   Qwen/Qwen2.5-Coder-7B-Instruct   Qwen/Qwen2.5-Math-7B-Instruct   Qwen/Qwen2.5-7B   Qwen/Qwen2.5-7B-Instruct
Merged ModelYes
Model Size7b
Required VRAM15.2 GB
Updated2025-10-15
MaintainerLocutusque
Model Typeqwen2
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   4.9 GB: 2-of-4   5.0 GB: 3-of-4   0.3 GB: 4-of-4
Supported Languagesen
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Context Length131072
Model Max Length131072
Transformers Version4.44.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than Locutusque/DareQwen-2.5-7B.

Rank the DareQwen 2.5 7B 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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