# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("EhimeNLP/AcademicRoBERTa")
model = AutoModelForMaskedLM.from_pretrained("EhimeNLP/AcademicRoBERTa")Quick Links
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Check out the documentation for more information.
Model description
We pretrained a RoBERTa-based Japanese masked language model on paper abstracts from the academic database CiNii Articles.
A Japanese Masked Language Model for Academic Domain
Vocabulary
The vocabulary consists of 32000 tokens including subwords induced by the unigram language model of sentencepiece.
license: apache-2.0
language:ja
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EhimeNLP/AcademicRoBERTa")