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Garrulus AWQ by TheBloke

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Garrulus AWQ is an open-source language model by TheBloke. Features: 7.2b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.11.

  4-bit   7b   Awq Base model:quantized:udkai/gar...   Base model:udkai/garrulus Dataset:hromi/winograd dpo bas...   Dpo   Mistral   Mlabonne/neuralmarcoro14-7b   Quantized   Region:us   Safetensors   Winograd
Model Card on HF 🤗: https://huggingface.co/TheBloke/Garrulus-AWQ 

Garrulus AWQ Benchmarks

LLME Score: 0.11468
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Garrulus AWQ (TheBloke/Garrulus-AWQ)
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Garrulus AWQ Parameters and Internals

Model Type 
mistral
Additional Notes 
This model was initially named 'ContaminatedWine' but was later named 'Garrulus' after an encounter with a eurasian jay. The model shows improved performance not only on Winogrande but also on TruthfulQA, HellaSwag, and ARC challenge metrics due to DPO contamination with Winogrande.
Training Details 
Data Sources:
mlabonne/NeuralMarcoro14-7B, hromi/winograd_dpo_basic
Methodology:
Intentionally contaminated with two epochs of direct preference optimization (DPO) with a slightly modified Winogrande dataset.
Training Time:
Few minutes on a A40
Hardware Used:
Hardware of Berlin University of the Arts (UDK-berlin)
LLM NameGarrulus AWQ
Repository 🤗https://huggingface.co/TheBloke/Garrulus-AWQ 
Model NameGarrulus
Model CreatorUDK dot AI
Base Model(s)  Garrulus   udkai/Garrulus
Model Size7.2b
Required VRAM4.2 GB
Updated2026-04-06
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Garrulus-AWQ.

Rank the Garrulus AWQ Capabilities

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Instruction Following and Task Automation  
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