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Qwen2.5 7B Instruct by nextvalueup

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  4bit   Autotrain compatible   Conversational   En   Endpoints compatible   Instruct   Pytorch   Quantized   Qwen2   Region:us   Sft   Sharded   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/nextvalueup/Qwen2.5-7B-Instruct 

Qwen2.5 7B Instruct Benchmarks

LLME Score: 0.1897
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 7B Instruct (nextvalueup/Qwen2.5-7B-Instruct)
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Qwen2.5 7B Instruct Parameters and Internals

LLM NameQwen2.5 7B Instruct
Repository 🤗https://huggingface.co/nextvalueup/Qwen2.5-7B-Instruct 
Base Model(s)  unsloth/qwen2.5-7b-instruct-bnb-4bit   unsloth/qwen2.5-7b-instruct-bnb-4bit
Model Size7b
Required VRAM15.2 GB
Updated2025-09-07
Maintainernextvalueup
Model Typeqwen2
Instruction-BasedYes
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 Length32768
Model Max Length32768
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 nextvalueup/Qwen2.5-7B-Instruct.

Rank the Qwen2.5 7B 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  
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