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Qwen2.5 0.5B Instruct F16 by viethq5

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Qwen2.5 0.5B Instruct F16 is an open-source language model by viethq5. Features: 0.5b LLM, VRAM: 1GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.17.

  Arxiv:2407.10671   Autotrain compatible Base model:finetune:qwen/qwen2...   Base model:qwen/qwen2.5-0.5b   Chat   Conversational   En   Endpoints compatible   Fp16   Instruct   Quantized   Qwen2   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/viethq5/Qwen2.5-0.5B-Instruct-f16 

Qwen2.5 0.5B Instruct F16 Benchmarks

LLME Score: 0.16796
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 F16 (viethq5/Qwen2.5-0.5B-Instruct-f16)
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Qwen2.5 0.5B Instruct F16 Parameters and Internals

LLM NameQwen2.5 0.5B Instruct F16
Repository 🤗https://huggingface.co/viethq5/Qwen2.5-0.5B-Instruct-f16 
Base Model(s)  Qwen/Qwen2.5-0.5B   Qwen/Qwen2.5-0.5B
Model Size0.5b
Required VRAM1 GB
Updated2025-09-23
Maintainerviethq5
Model Typeqwen2
Instruction-BasedYes
Model Files  1.0 GB
Supported Languagesen
Quantization Typefp16
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.43.1
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 viethq5/Qwen2.5-0.5B-Instruct-f16.

Rank the Qwen2.5 0.5B Instruct F16 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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