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Sejong Qwen Test V3 by SejongKRX

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  4bit   Autotrain compatible   En   Endpoints compatible   Krx   Pytorch   Quantized   Qwen2   Region:us   Sharded   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/SejongKRX/Sejong-Qwen-test-v3 

Sejong Qwen Test V3 Benchmarks

LLME Score: 0.21327
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Sejong Qwen Test V3 (SejongKRX/Sejong-Qwen-test-v3)

Sejong Qwen Test V3 Parameters and Internals

LLM NameSejong Qwen Test V3
Repository 🤗https://huggingface.co/SejongKRX/Sejong-Qwen-test-v3 
Base Model(s)  unsloth/qwen2.5-7b-bnb-4bit   unsloth/qwen2.5-7b-bnb-4bit
Model Size7b
Required VRAM15.2 GB
Updated2025-05-15
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 Version4.46.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|PAD_TOKEN|>
Vocabulary Size152064
Torch Data Typefloat16
Errorsreplace

Best Alternatives to Sejong Qwen Test V3

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2.5 7B Instruct 1M 4bit986K / 4.3 GB5738
...B Instruct 1M Unsloth Bnb 4bit986K / 7.5 GB4252
Qwen2.5 7B Instruct 1M 8bit986K / 8.1 GB403
Qwen2.5 7B Instruct 1M 6bit986K / 6.2 GB152
...still Qwen 7B Unsloth Bnb 4bit128K / 8.5 GB2746119
Gte Qwen2 7B Instruct 4bit DWQ128K / 4.3 GB722
Mini Pathfinder128K / 15.2 GB160
Zira Z.1128K / 15.2 GB3180
A1 V002128K / 15.2 GB70
Nocturnia 8B 1128K / 15.2 GB681
Note: green Score (e.g. "73.2") means that the model is better than SejongKRX/Sejong-Qwen-test-v3.

Rank the Sejong Qwen Test V3 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
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Text Summarization and Feature Extraction  
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Multi-Language Support and Translation  

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Release v20241227
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