QwQ 32B Preview AWQ by KirillR

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  Arxiv:2407.10671   4-bit   Autotrain compatible   Awq Base model:quantized:qwen/qwq-... Base model:qwen/qwq-32b-previe...   Conversational   En   Endpoints compatible   Quantized   Qwen2   Region:us   Safetensors   Sharded   Tensorflow

QwQ 32B Preview AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
QwQ 32B Preview AWQ (KirillR/QwQ-32B-Preview-AWQ)

QwQ 32B Preview AWQ Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
research
Applications:
mathematics, coding
Primary Use Cases:
AI reasoning in mathematics and coding
Limitations:
Language Mixing and Code Switching, Recursive Reasoning Loops, Performance limitations in common sense reasoning and nuanced language understanding
Additional Notes 
The quantized model significantly reduces memory usage and computational requirements, making it suitable for deployment on hardware with limited resources.
Supported Languages 
en (proficient)
Responsible Ai Considerations 
Mitigation Strategies:
Enhanced safety measures are needed to ensure reliable and secure performance.
LLM NameQwQ 32B Preview AWQ
Repository ๐Ÿค—https://huggingface.co/KirillR/QwQ-32B-Preview-AWQ 
Base Model(s)  QwQ 32B Preview   Qwen/QwQ-32B-Preview
Model Size32b
Required VRAM19.4 GB
Updated2024-12-08
MaintainerKirillR
Model Typeqwen2
Model Files  3.9 GB: 1-of-5   4.0 GB: 2-of-5   4.0 GB: 3-of-5   4.0 GB: 4-of-5   3.5 GB: 5-of-5
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.46.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than KirillR/QwQ-32B-Preview-AWQ.

Rank the QwQ 32B Preview AWQ 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 v20241124