Qwen2.5 14B Bnb 4bit by unsloth

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Qwen2.5 14B Bnb 4bit Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Qwen2.5 14B Bnb 4bit Parameters and Internals

Model Type 
Causal Language Model
Use Cases 
Areas:
Research, Coding, Mathematics, Multilingual Applications
Applications:
Chatbots, Structured Data Understanding, Role-playing Implementations
Primary Use Cases:
instruction following, generating long texts, understanding structured data, generating structured outputs
Limitations:
Not recommended for conversations without further training
Considerations:
Use post-training methods for conversations like SFT, RLHF
Additional Notes 
Supports multilingual capabilities with improved role-play conditions for chatbots.
Supported Languages 
English (high), Chinese (high), French (medium), Spanish (medium), Portuguese (medium), German (medium), Italian (medium), Russian (medium), Japanese (medium), Korean (medium), Vietnamese (medium), Thai (medium), Arabic (medium), other_languages (basic)
Training Details 
Data Sources:
specialized expert models in coding and mathematics
Context Length:
131072
Model Architecture:
transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Use the latest version of 'transformers' to avoid errors.
LLM NameQwen2.5 14B Bnb 4bit
Repository ๐Ÿค—https://huggingface.co/unsloth/Qwen2.5-14B-bnb-4bit 
Base Model(s)  Qwen/Qwen2.5-14B   Qwen/Qwen2.5-14B
Model Size14b
Required VRAM9.9 GB
Updated2025-06-09
Maintainerunsloth
Model Typeqwen2
Model Files  5.0 GB: 1-of-2   4.9 GB: 2-of-2
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.49.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|vision_pad|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace
Qwen2.5 14B Bnb 4bit (unsloth/Qwen2.5-14B-bnb-4bit)

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Note: green Score (e.g. "73.2") means that the model is better than unsloth/Qwen2.5-14B-bnb-4bit.

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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 v20241124