File size: 1,431 Bytes
2cca4df 80dd97b 2cca4df |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 |
---
language: ja
thumbnail: https://github.com/rinnakk/japanese-gpt2/blob/master/rinna.png
tags:
- ja
- japanese
- gpt2
- text-generation
- lm
- nlp
license: mit
datasets:
- cc100
- wikipedia
---
# japanese-gpt2-xsmall
![rinna-icon](./rinna.png)
This repository provides an extra-small-sized Japanese GPT-2 model. The model is provided by [rinna](https://corp.rinna.co.jp/).
# How to use the model
*NOTE:* Use `T5Tokenizer` to initiate the tokenizer.
~~~~
from transformers import T5Tokenizer, GPT2LMHeadModel
tokenizer = T5Tokenizer.from_pretrained("rinna/japanese-gpt2-small")
tokenizer.do_lower_case = True # due to some bug of tokenizer config loading
model = GPT2LMHeadModel.from_pretrained("rinna/japanese-gpt2-small")
~~~~
# Model architecture
A 6-layer, 512-hidden-size transformer-based language model.
# Training
The model was trained on [Japanese CC-100](http://data.statmt.org/cc-100/ja.txt.xz) and [Japanese Wikipedia](https://dumps.wikimedia.org/other/cirrussearch) to optimize a traditional language modelling objective on 8\\*V100 GPUs for around 4 days. It reaches around 28 perplexity on a chosen validation set from CC-100.
# Tokenization
The model uses a [sentencepiece](https://github.com/google/sentencepiece)-based tokenizer, the vocabulary was trained on the Japanese Wikipedia using the official sentencepiece training script.
# Licenese
[The MIT license](https://opensource.org/licenses/MIT)
|