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Qwen2.5 14B Instruct by braindao

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Qwen2.5 14B Instruct is an open-source language model by braindao. Features: 14b LLM, VRAM: 29.6GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.3.

  Arxiv:2309.00071   Arxiv:2407.10671 Base model:finetune:qwen/qwen2...   Base model:qwen/qwen2.5-14b   Chat   Conversational   En   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/braindao/Qwen2.5-14B-Instruct 

Qwen2.5 14B Instruct Benchmarks

MMLU Pro: 43.22
GPQA: 10.51
MUSR: 10.62
BBH: 48.57
IFEval: 81.43 vs 88 (so35)-7.5%
MATH Lvl 5: 55.29
LLME Score: 0.30461
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 14B Instruct (braindao/Qwen2.5-14B-Instruct)
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Qwen2.5 14B Instruct Parameters and Internals

LLM NameQwen2.5 14B Instruct
Repository 🤗https://huggingface.co/braindao/Qwen2.5-14B-Instruct 
Base Model(s)  Qwen/Qwen2.5-14B   Qwen/Qwen2.5-14B
Model Size14b
Required VRAM29.6 GB
Updated2026-04-02
Maintainerbraindao
Model Typeqwen2
Instruction-BasedYes
Model Files  3.9 GB: 1-of-8   4.0 GB: 2-of-8   4.0 GB: 3-of-8   4.0 GB: 4-of-8   4.0 GB: 5-of-8   4.0 GB: 6-of-8   4.0 GB: 7-of-8   1.7 GB: 8-of-8
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.43.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Qwen2.5 14B Instruct 1M986K / 29.6 GB4468332
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ZYH LLM Qwen2.5 14B V4986K / 29.7 GB218
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Qwen2.5 14B YOYO V4986K / 29.7 GB145
Qwen2.5 14B YOYO Latest V2986K / 29.7 GB1290
...14B Instruct 1M GRPO Reasoning986K / 29.7 GB414
Impish QWEN 14B 1M986K / 29.7 GB3924
Q2.5 14B Instruct 1M Harmony986K / 29.7 GB31
Note: green Score (e.g. "73.2") means that the model is better than braindao/Qwen2.5-14B-Instruct.

Rank the Qwen2.5 14B Instruct 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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