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Qwen2.5 3B Instruct Chat Sft by binhphap5

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Qwen2.5 3B Instruct Chat Sft is an open-source language model by binhphap5. Features: 3b LLM, VRAM: 6.2GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.21.

  4bit   Autotrain compatible   Conversational   En   Endpoints compatible   Instruct   Quantized   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/binhphap5/Qwen2.5-3B-Instruct-Chat-sft 

Qwen2.5 3B Instruct Chat Sft Benchmarks

LLME Score: 0.20807
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 3B Instruct Chat Sft (binhphap5/Qwen2.5-3B-Instruct-Chat-sft)
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Qwen2.5 3B Instruct Chat Sft Parameters and Internals

LLM NameQwen2.5 3B Instruct Chat Sft
Repository 🤗https://huggingface.co/binhphap5/Qwen2.5-3B-Instruct-Chat-sft 
Base Model(s)  unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit   unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit
Model Size3b
Required VRAM6.2 GB
Updated2025-09-23
Maintainerbinhphap5
Model Typeqwen2
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   1.2 GB: 2-of-2
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.51.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|vision_pad|>
Vocabulary Size151936
Torch Data Typefloat16
Errorsreplace

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Athena 1 3B32K / 6.2 GB31
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...2.5 Coder 3B Instruct Bnb 4bit32K / 2 GB127066
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Model 16bit32K / 6.2 GB70
Note: green Score (e.g. "73.2") means that the model is better than binhphap5/Qwen2.5-3B-Instruct-Chat-sft.

Rank the Qwen2.5 3B Instruct Chat Sft 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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