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EEVE Korean Instruct 10.8B V1.0 AWQ by Copycats

 »  All LLMs  »  Copycats  »  EEVE Korean Instruct 10.8B V1.0 AWQ   URL Share it on

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EEVE Korean Instruct 10.8B V1.0 AWQ is an open-source language model by Copycats. Features: 10.8b LLM, VRAM: 6.1GB, Context: 4K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

  4-bit   Awq Base model:quantized:yanolja/y... Base model:yanolja/yanoljanext...   Conversational   Instruct   Ko   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Copycats/EEVE-Korean-Instruct-10.8B-v1.0-AWQ 

EEVE Korean Instruct 10.8B V1.0 AWQ Benchmarks

LLME Score: 0.12632
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
EEVE Korean Instruct 10.8B V1.0 AWQ (Copycats/EEVE-Korean-Instruct-10.8B-v1.0-AWQ)
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EEVE Korean Instruct 10.8B V1.0 AWQ Parameters and Internals

Model Type 
text generation
Additional Notes 
AWQ is a low-bit weight quantization method supporting 4-bit quantization, offering faster Transformers-based inference with equivalent or better quality compared to GPTQ.
Supported Languages 
ko (full)
LLM NameEEVE Korean Instruct 10.8B V1.0 AWQ
Repository 🤗https://huggingface.co/Copycats/EEVE-Korean-Instruct-10.8B-v1.0-AWQ 
Base Model(s)  yanolja/EEVE-Korean-Instruct-10.8B-v1.0   yanolja/EEVE-Korean-Instruct-10.8B-v1.0
Model Size10.8b
Required VRAM6.1 GB
Updated2026-04-29
MaintainerCopycats
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   1.1 GB: 2-of-2
Supported Languagesko
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size40960
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than Copycats/EEVE-Korean-Instruct-10.8B-v1.0-AWQ.

Rank the EEVE Korean Instruct 10.8B V1.0 AWQ 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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