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Qwen3 4B Instruct 2507 Sft Full by Nofing

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Qwen3 4B Instruct 2507 Sft Full is an open-source language model by Nofing. Features: 4b LLM, VRAM: 8.1GB, Context: 256K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.2.

  4bit   Autotrain compatible   Conversational   En   Endpoints compatible   Instruct   Quantized   Qwen3   Region:us   Safetensors   Sharded   Tensorflow   Unsloth
Model Card on HF 🤗: https://huggingface.co/Nofing/qwen3-4B-Instruct-2507-sft-full 

Qwen3 4B Instruct 2507 Sft Full Benchmarks

LLME Score: 0.20428
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen3 4B Instruct 2507 Sft Full (Nofing/qwen3-4B-Instruct-2507-sft-full)
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Qwen3 4B Instruct 2507 Sft Full Parameters and Internals

LLM NameQwen3 4B Instruct 2507 Sft Full
Repository 🤗https://huggingface.co/Nofing/qwen3-4B-Instruct-2507-sft-full 
Base Model(s)  unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit   unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit
Model Size4b
Required VRAM8.1 GB
Updated2025-09-23
MaintainerNofing
Model Typeqwen3
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   3.1 GB: 2-of-2
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen3ForCausalLM
Licenseapache-2.0
Context Length262144
Model Max Length262144
Transformers Version4.54.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|vision_pad|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than Nofing/qwen3-4B-Instruct-2507-sft-full.

Rank the Qwen3 4B Instruct 2507 Sft Full 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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