Qwen2 0.5B Instruct by Qwen

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

Qwen2 0.5B Instruct Parameters and Internals

Model Type 
text-generation
Training Details 
Methodology:
We pretrained the models with a large amount of data, and we post-trained the models with both supervised finetuning and direct preference optimization.
Model Architecture:
Transformer architecture with SwiGLU activation, attention QKV bias, group query attention, etc.
LLM NameQwen2 0.5B Instruct
Repository ๐Ÿค—https://huggingface.co/Qwen/Qwen2-0.5B-Instruct 
Base Model(s)  Qwen/Qwen2-0.5B   Qwen/Qwen2-0.5B
Model Size0.5b
Required VRAM1 GB
Updated2025-02-05
MaintainerQwen
Model Typeqwen2
Instruction-BasedYes
Model Files  1.0 GB
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.40.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Quantized Models of the Qwen2 0.5B Instruct

Model
Likes
Downloads
VRAM
Qwen2 0.5B Instruct GGUF1160220 GB
Qwen2 0.5B Instruct GPTQ Int4125880 GB
Qwen2 0.5B 16bit0521 GB
Qwen2 0.5B Instruct GPTQ Int821111 GB
Qwen2 0.5B Instruct AWQ3730 GB
Qwen2 0.5B Instruct GGUF0310 GB

Best Alternatives to Qwen2 0.5B Instruct

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2 0.5B Abyme Merge3128K / 1.3 GB550
Qwen2 0.5B Abyme Merge2128K / 0.3 GB460
Qwen2.5 0.5B Instruct32K / 1 GB696164198
QwQ 0.5B Distilled SFT32K / 1 GB479121
Lb Reranker 0.5B V1.032K / 1 GB230361
Qwen2.5 Coder 0.5B Instruct32K / 1 GB2925331
FastThink 0.5B Tiny32K / 1 GB2509
Qwen2.5 0.5B Instruct ITA32K / 1 GB29152
QwenStock 0.5B32K / 1.3 GB2550
Qwen2.5 0.5B Instruct SFT32K / 1.3 GB1431
Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2-0.5B-Instruct.

Rank the Qwen2 0.5B Instruct Capabilities

๐Ÿ†˜ 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! ๐ŸŒŸ

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 v20241227