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Quyen V0.1 AWQ by LoneStriker

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  4-bit   Awq   Conversational Dataset:argilla/distilabel-cap...   Dataset:intel/orca dpo pairs   Dataset:ldjnr/capybara   Dataset:teknium/openhermes-2.5   En   Endpoints compatible   Pytorch   Quantized   Qwen2   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/LoneStriker/Quyen-v0.1-AWQ 

Quyen V0.1 AWQ Benchmarks

LLME Score: 0.13296
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Quyen V0.1 AWQ (LoneStriker/Quyen-v0.1-AWQ)
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Quyen V0.1 AWQ Parameters and Internals

Model Type 
text generation
Additional Notes 
Acknowledgement: Grateful to Tensoic and Ontocord for support with compute and data preparation. Special thanks to the Qwen team.
Supported Languages 
en (English)
Training Details 
Data Sources:
teknium/OpenHermes-2.5, LDJnr/Capybara, Intel/orca_dpo_pairs, argilla/distilabel-capybara-dpo-7k-binarized, Private Data by Ontocord & BEE-spoke-data
Methodology:
Trained with SFT and DPO
Input Output 
Input Format:
ChatML as the default template
Accepted Modalities:
text
LLM NameQuyen V0.1 AWQ
Repository 🤗https://huggingface.co/LoneStriker/Quyen-v0.1-AWQ 
Model Size4b
Required VRAM3.2 GB
Updated2026-02-05
MaintainerLoneStriker
Model Typeqwen2
Model Files  3.2 GB
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.37.1
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 LoneStriker/Quyen-v0.1-AWQ.

Rank the Quyen V0.1 AWQ Capabilities

🆘 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! 🌟

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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Release v20241124
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