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Llama 3 Korean 8B AWQ by sh2orc

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Llama 3 Korean 8B AWQ is an open-source language model by sh2orc. Features: 8b LLM, VRAM: 6GB, Context: 8K, License: llama3, Quantized, LLM Explorer Score: 0.13.

  4-bit   Awq   Conversational   Endpoints compatible   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/sh2orc/llama-3-korean-8b-awq 

Llama 3 Korean 8B AWQ Benchmarks

LLME Score: 0.13378
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 3 Korean 8B AWQ (sh2orc/llama-3-korean-8b-awq)
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Llama 3 Korean 8B AWQ Parameters and Internals

Model Type 
Foundation Model
Use Cases 
Areas:
Research, Text generation
Applications:
Ai assistant, Chatbot interactions
Primary Use Cases:
Generating responses to queries, Elaborating on user input
Supported Languages 
languages (Korean), proficiency (Native proficiency)
Training Details 
Data Sources:
Koalpaca v1.1a, korean_safe_conversation
Methodology:
Paged Attention, AWQ quantization
Input Output 
Input Format:
Tokenized input using pre-trained tokenizer
Accepted Modalities:
Text
Output Format:
Generated text
LLM NameLlama 3 Korean 8B AWQ
Repository 🤗https://huggingface.co/sh2orc/llama-3-korean-8b-awq 
Base Model(s)  Llama 3 Korean 8B   sh2orc/Llama-3-Korean-8B
Model Size8b
Required VRAM6 GB
Updated2026-04-07
Maintainersh2orc
Model Typellama
Model Files  4.8 GB: 1-of-2   1.2 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensellama3
Context Length8192
Model Max Length8192
Transformers Version4.40.2
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
Vocabulary Size145088
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than sh2orc/llama-3-korean-8b-awq.

Rank the Llama 3 Korean 8B 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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