Kogpt Neox Tiny by heegyu

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Kogpt Neox Tiny is an open-source language model by heegyu. Features: LLM, VRAM: 0.1GB, Context: 0.5K, License: mit, LLM Explorer Score: 0.04.

  Endpoints compatible   Gpt neox   Pytorch   Region:us
Model Card on HF ๐Ÿค—: https://huggingface.co/heegyu/kogpt-neox-tiny 

Kogpt Neox Tiny Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Kogpt Neox Tiny (heegyu/kogpt-neox-tiny)
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Kogpt Neox Tiny Parameters and Internals

Model Type 
Language Model, Text Generation
Use Cases 
Areas:
Research, Development
Applications:
Text generation, Dialogue systems
Primary Use Cases:
Text completion, Text generation for dialogues
Supported Languages 
Korean (Proficient)
Training Details 
Data Sources:
AIHub SNS ๋Œ€ํ™” (747MB), AIHub ๊ตฌ์–ด์ฒด (435MB), ํ•œ๊ตญ์–ด ์œ„ํ‚ค (773MB), ๋‚˜๋ฌด์œ„ํ‚ค (5.8GB), ๊ตญ๋ฆฝ๊ตญ์–ด์› ๋ฉ”์‹ ์ € ๋Œ€ํ™” (21MB)
Context Length:
512
Training Time:
2 days 17 hours
Hardware Used:
NVIDIA Tesla T4 (16GB VRAM)
Model Architecture:
GPT-Neo-X (Pytorch), 2 Layers, 512 hidden dim, 2048 intermediate, 8 heads, 8000 vocab size
Input Output 
Input Format:
Text input
Accepted Modalities:
Text
Output Format:
Generated text
LLM NameKogpt Neox Tiny
Repository ๐Ÿค—https://huggingface.co/heegyu/kogpt-neox-tiny 
Required VRAM0.1 GB
Updated2026-04-04
Maintainerheegyu
Model Typegpt_neox
Model Files  0.1 GB
Model ArchitectureGPTNeoXForCausalLM
Licensemit
Context Length512
Model Max Length512
Transformers Version4.24.0
Tokenizer ClassGPT2Tokenizer
Beginning of Sentence Token<|endoftext|>
End of Sentence Token<|endoftext|>
Unk Token<|endoftext|>
Vocabulary Size8000
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than heegyu/kogpt-neox-tiny.

Rank the Kogpt Neox Tiny 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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Release v20260328a