Upload README.md

README.md

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+---
+language:
+  - ko
+tags:
+- generated_from_keras_callback
+model-index:
+- name: RoBERTa-large-Detection-P2G
+  results: []
+---
+
+# RoBERTa-large-Detection-P2G
+
+
+이 모델은 klue/roberta-large을 국립 국어원 신문 말뭉치 5만개의 문장을 2021을 g2pK로 훈련시켜 G2P된 데이터를 탐지합니다.
+
+
+## Usage
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import torch
+import numpy as np
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model_dir = "kfkas/RoBERTa-large-Detection-P2G"
+tokenizer = AutoTokenizer.from_pretrained(model_dir)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_dir)
+
+text = "월드커 파나은행 대표티메 행우늬 이달러 이영영장 선물"
+with torch.no_grad():
+    x = tokenizer(text, padding='max_length', truncation=True, return_tensors='pt', max_length=128)
+    y_pred = model(x["input_ids"].to(device))
+    logits = y_pred.logits
+    y_pred = logits.detach().cpu().numpy()
+    y = np.argmax(y_pred)
+    print(y)
+    #1
+```
+
+
+## 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