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Bilingual GPT Neox 4B 8K by rinna

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  Arxiv:2306.15595   Arxiv:2404.01657   Autotrain compatible Base model:finetune:rinna/bili... Base model:rinna/bilingual-gpt...   Dataset:cc100   Dataset:eleutherai/pile   Dataset:mc4 Dataset:togethercomputer/redpa...   Dataset:wikipedia   En   Ext 8k   Gpt neox   Ja   Pytorch   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/rinna/bilingual-gpt-neox-4b-8k 

Bilingual GPT Neox 4B 8K Benchmarks

ARC: 28.58 vs 96.7 (so35)-70.4%
HellaSwag: 43.94 vs 95.3 (gpt4)-53.9%
MMLU: 25.38 vs 88.3 (so35)-71.3%
TruthfulQA: 47.48 vs 59 (gpt4)-19.5%
WinoGrande: 47.99 vs 87.5 (gpt4)-45.2%
LLME Score: 0.14682
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Bilingual GPT Neox 4B 8K (rinna/bilingual-gpt-neox-4b-8k)
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Bilingual GPT Neox 4B 8K Parameters and Internals

Model Type 
bilingual, language model, transformer-based
Use Cases 
Areas:
research, commercial applications
Additional Notes 
The model's standard configuration requires transformers version 4.31.0 or higher to operate correctly. Special attention to hyper-parameters is needed for optimal performance.
Supported Languages 
English (proficient), Japanese (proficient)
Training Details 
Data Sources:
Japanese CC-100, Japanese C4, The Pile, Redpajama, Wikipedia
Data Volume:
1.5 billion tokens
Methodology:
fine-tuning using RoPE positional interpolation
Context Length:
8192
Model Architecture:
A 36-layer, 2816-hidden-size transformer-based language model
Input Output 
Performance Tips:
Since the model is sensitive to decoding hyper-parameters (e.g., temperature, top_p, top_k, repetition_penalty), it is suggested to explore the best setting for your task.
LLM NameBilingual GPT Neox 4B 8K
Repository 🤗https://huggingface.co/rinna/bilingual-gpt-neox-4b-8k 
Base Model(s)  Bilingual GPT Neox 4B   rinna/bilingual-gpt-neox-4b
Model Size4b
Required VRAM7.7 GB
Updated2025-10-04
Maintainerrinna
Model Typegpt_neox
Model Files  7.7 GB   7.7 GB
Supported Languagesja en
Context Length8k
Model ArchitectureGPTNeoXForCausalLM
Licensemit
Context Length2048
Model Max Length2048
Tokenizer ClassT5Tokenizer
Padding Token[PAD]
Vocabulary Size65536
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than rinna/bilingual-gpt-neox-4b-8k.

Rank the Bilingual GPT Neox 4B 8K Capabilities

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Instruction Following and Task Automation  
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