Japanese GPT Neox 3.6B by rinna

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  Arxiv:2404.01657   Autotrain compatible   Dataset:cc100   Dataset:mc4   Dataset:wikipedia   Gpt neox   Ja   Lm   Pytorch   Region:us   Safetensors

Japanese GPT Neox 3.6B Benchmarks

Japanese GPT Neox 3.6B (rinna/japanese-gpt-neox-3.6b)
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Japanese GPT Neox 3.6B Parameters and Internals

Model Type 
text generation, nlp
Additional Notes 
The model uses sentencepiece tokenizer with specific configurations such as byte fallback and `-add_dummy_prefix` turned off.
Training Details 
Data Sources:
Japanese CC-100, Japanese C4, Japanese Wikipedia
Data Volume:
312.5B tokens
Methodology:
traditional language modelling objective
Model Architecture:
A 36-layer, 2816-hidden-size transformer-based language model
Input Output 
Performance Tips:
set use_fast=False to make certain features function correctly.
LLM NameJapanese GPT Neox 3.6B
Repository ๐Ÿค—https://huggingface.co/rinna/japanese-gpt-neox-3.6b 
Model Size3.6b
Required VRAM7.4 GB
Updated2025-08-28
Maintainerrinna
Model Typegpt_neox
Model Files  7.4 GB   7.4 GB
Supported Languagesja
Model ArchitectureGPTNeoXForCausalLM
Licensemit
Context Length2048
Model Max Length2048
Tokenizer ClassT5Tokenizer
Padding Token[PAD]
Vocabulary Size32000
Torch Data Typefloat16

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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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124