Qwen2.5 0.5B Instruct by Qwen

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  Arxiv:2407.10671   Autotrain compatible Base model:finetune:qwen/qwen2...   Base model:qwen/qwen2.5-0.5b   Chat   Conversational   En   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors

Qwen2.5 0.5B Instruct Benchmarks

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 (Qwen/Qwen2.5-0.5B-Instruct)

Qwen2.5 0.5B Instruct Parameters and Internals

Model Type 
Causal Language Model
Use Cases 
Areas:
Chat applications, Multilingual text generation
Applications:
Role-play chatbots, Long text generation
Primary Use Cases:
Coding, Mathematics
Limitations:
Limited understanding of unsupported languages
Supported Languages 
English (High), Chinese (High), French (Medium), Spanish (Medium), Portuguese (Medium), German (Medium), Italian (Medium), Russian (Medium), Japanese (Medium), Korean (Medium), Vietnamese (Medium), Thai (Medium), Arabic (Medium)
Training Details 
Methodology:
Pretraining & Post-training
Context Length:
32768
Model Architecture:
Transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias and tied word embeddings
Input Output 
Input Format:
Chat template with system and user roles
Accepted Modalities:
text
Output Format:
Text
Performance Tips:
Use the latest `transformers` library for optimal performance.
LLM NameQwen2.5 0.5B Instruct
Repository ๐Ÿค—https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct 
Base Model(s)  Qwen/Qwen2.5-0.5B   Qwen/Qwen2.5-0.5B
Model Size0.5b
Required VRAM1 GB
Updated2024-12-21
MaintainerQwen
Model Typeqwen2
Instruction-BasedYes
Model Files  1.0 GB
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.43.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Quantized Models of the Qwen2.5 0.5B Instruct

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Acrux 500M O1 Journey72471 GB
Qwen2.5 0.5B Instruct Bnb 4bit299550 GB
Qwen2.5 0.5B Instruct AWQ527160 GB
...wen2.5 0.5B Instruct GPTQ Int4424920 GB
...wen2.5 0.5B Instruct GPTQ Int868300 GB

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Rank the Qwen2.5 0.5B Instruct 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217