T5Tokenizer to initiate the tokenizer.
from transformers import T5Tokenizer, AutoModelForCausalLM tokenizer = T5Tokenizer.from_pretrained("rinna/japanese-gpt2-medium") tokenizer.do_lower_case = True # due to some bug of tokenizer config loading model = AutoModelForCausalLM.from_pretrained("rinna/japanese-gpt2-medium")
A 24-layer, 1024-hidden-size transformer-based language model.
The model was trained on Japanese CC-100 and Japanese Wikipedia to optimize a traditional language modelling objective on 8\*V100 GPUs for around 30 days. It reaches around 18 perplexity on a chosen validation set from the same data.
The model uses a sentencepiece-based tokenizer, the vocabulary was trained on the Japanese Wikipedia using the official sentencepiece training script.
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