Sejong Qwen V5 by SejongKRX

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  4bit   Autotrain compatible   En   Endpoints compatible   Krx   Pytorch   Quantized   Qwen2   Region:us   Sharded   Trl   Unsloth

Sejong Qwen V5 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Sejong Qwen V5 (SejongKRX/Sejong-Qwen-v5)

Sejong Qwen V5 Parameters and Internals

LLM NameSejong Qwen V5
Repository ๐Ÿค—https://huggingface.co/SejongKRX/Sejong-Qwen-v5 
Base Model(s)  unsloth/qwen2.5-7b-bnb-4bit   unsloth/qwen2.5-7b-bnb-4bit
Model Size7b
Required VRAM15.2 GB
Updated2025-02-22
MaintainerSejongKRX
Model Typeqwen2
Model Files  4.9 GB: 1-of-4   4.9 GB: 2-of-4   4.3 GB: 3-of-4   1.1 GB: 4-of-4
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.44.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|PAD_TOKEN|>
Vocabulary Size152064
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than SejongKRX/Sejong-Qwen-v5.

Rank the Sejong Qwen V5 Capabilities

๐Ÿ†˜ Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! ๐ŸŒŸ

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