Japanese Distilgpt2 by knok

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  Dataset:cc100   Dataset:wikipedia   Endpoints compatible   Gpt2   Ja   Japanese   Lm   Pytorch   Region:us   Safetensors

Japanese Distilgpt2 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Japanese Distilgpt2 (knok/japanese-distilgpt2)

Japanese Distilgpt2 Parameters and Internals

Model Type 
text-generation, language model
Supported Languages 
Japanese (Full)
Training Details 
Data Sources:
Wikipedia
Methodology:
Distillation
Training Time:
4 months
Hardware Used:
A100 x4 on a2-highgpu-4 instance
Input Output 
Accepted Modalities:
text
Performance Tips:
Use tokenizer from rinna/japanese-gpt2-medium.
LLM NameJapanese Distilgpt2
Repository ๐Ÿค—https://huggingface.co/knok/japanese-distilgpt2 
Model Size115.7m
Required VRAM0.4 GB
Updated2025-02-22
Maintainerknok
Model Typegpt2
Model Files  0.4 GB   0.4 GB
Supported Languagesja
Model ArchitectureAutoModel
Licensemit
Transformers Version4.15.0
Vocabulary Size32000
Activation Functiongelu_new

Rank the Japanese Distilgpt2 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227