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Qwen Indo SFT by AFP7

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Qwen Indo SFT is an open-source language model by AFP7. Features: 3b LLM, VRAM: 6.2GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.26.

  4bit Base model:finetune:unsloth/qw... Base model:unsloth/qwen2.5-3b-...   Conversational   En   Endpoints compatible   Instruct   Quantized   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Unsloth
Model Card on HF 🤗: https://huggingface.co/AFP7/Qwen-Indo-SFT 

Qwen Indo SFT Benchmarks

LLME Score: 0.25653
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen Indo SFT (AFP7/Qwen-Indo-SFT)
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Qwen Indo SFT Parameters and Internals

LLM NameQwen Indo SFT
Repository 🤗https://huggingface.co/AFP7/Qwen-Indo-SFT 
Base Model(s)  unsloth/Qwen2.5-3B-Instruct-bnb-4bit   unsloth/Qwen2.5-3B-Instruct-bnb-4bit
Model Size3b
Required VRAM6.2 GB
Updated2026-06-25
MaintainerAFP7
Model Typeqwen2
Instruction-BasedYes
Model Files  4.0 GB: 1-of-2   2.2 GB: 2-of-2
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than AFP7/Qwen-Indo-SFT.

Rank the Qwen Indo SFT Capabilities

🆘 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! 🌟

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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