Bilingual GPT Neox 4B by rinna

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  Arxiv:2404.01657   Autotrain compatible   Dataset:cc100   Dataset:eleutherai/pile   Dataset:mc4 Dataset:togethercomputer/redpa...   Dataset:wikipedia   En   Gpt neox   Ja   Pytorch   Region:us   Safetensors

Bilingual GPT Neox 4B Benchmarks

Bilingual GPT Neox 4B (rinna/bilingual-gpt-neox-4b)

Bilingual GPT Neox 4B Parameters and Internals

Model Type 
bilingual, text generation
Supported Languages 
ja (native), en (proficient)
Training Details 
Data Sources:
Japanese CC-100, mc4, EleutherAI/pile, togethercomputer/RedPajama-Data-1T, Wikipedia
Data Volume:
524B tokens
Methodology:
36-layer, 2816-hidden-size transformer
Model Architecture:
transformer-based language model
Input Output 
Accepted Modalities:
text
Performance Tips:
Since the model is sensitive to decoding hyper-parameters, it is suggested to explore the best setting for your task.
LLM NameBilingual GPT Neox 4B
Repository ๐Ÿค—https://huggingface.co/rinna/bilingual-gpt-neox-4b 
Model Size4b
Required VRAM7.7 GB
Updated2024-12-26
Maintainerrinna
Model Typegpt_neox
Model Files  7.7 GB   7.7 GB
Supported Languagesja en
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.

Rank the Bilingual GPT Neox 4B 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217