t5-large-korean-P2G
이 모델은 lcw99 / t5-large-korean-text-summary을 국립 국어원 신문 말뭉치 50만개의 문장을 2021을 g2pK로 훈련시켜 G2P된 데이터를 원본으로 돌립니다. git : https://github.com/taemin6697
Usage
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
model_dir = "kfkas/t5-large-korean-P2G"
tokenizer = AutoTokenizer.from_pretrained(model_dir)
model = AutoModelForSeq2SeqLM.from_pretrained(model_dir)
text = "서규왕국 싸우디 태양광·풍녁 빨쩐 중심지 될 껃"
inputs = tokenizer.encode(text,return_tensors="pt")
output = model.generate(inputs)
decoded_output = tokenizer.batch(output[0], skip_special_tokens=True)
print(decoded_output)#석유왕국 사우디 태양광·풍력 발전 중심지 될 것
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float16
Training results
Framework versions
- Transformers 4.22.1
- TensorFlow 2.10.0
- Datasets 2.5.1
- Tokenizers 0.12.1