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Qwen2.5 0.5B Instruct GPTQ Int8 by Qwen

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Qwen2.5 0.5B Instruct GPTQ Int8 is an open-source language model by Qwen. Features: 0.5b LLM, VRAM: 0.6GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.17.

  Arxiv:2407.10671   8-bit Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-0.5b-i...   Chat   Conversational   En   Endpoints compatible   Gptq   Instruct   Quantized   Qwen2   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int8 

Qwen2.5 0.5B Instruct GPTQ Int8 Benchmarks

LLME Score: 0.16561
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 0.5B Instruct GPTQ Int8 (Qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int8)
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Qwen2.5 0.5B Instruct GPTQ Int8 Parameters and Internals

Model Type 
Causal Language Models
Additional Notes 
The Qwen2.5 model offers significant improvements in coding and mathematics, long-context support, multilingual capabilities, and enhanced instruction-following.
Supported Languages 
en (English), zh (Chinese), fr (French), es (Spanish), pt (Portuguese), de (German), it (Italian), ru (Russian), ja (Japanese), ko (Korean), vi (Vietnamese), th (Thai), ar (Arabic)
Training Details 
Methodology:
Pretraining & Post-training
Context Length:
32768
Model Architecture:
transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias and tied word embeddings
LLM NameQwen2.5 0.5B Instruct GPTQ Int8
Repository 🤗https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int8 
Base Model(s)  Qwen/Qwen2.5-0.5B-Instruct   Qwen/Qwen2.5-0.5B-Instruct
Model Size0.5b
Required VRAM0.6 GB
Updated2026-04-05
MaintainerQwen
Model Typeqwen2
Instruction-BasedYes
Model Files  0.6 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.39.3
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 Qwen/Qwen2.5-0.5B-Instruct-GPTQ-Int8.

Rank the Qwen2.5 0.5B Instruct GPTQ Int8 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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