| # Arabic EOU Detection Model | |
| Fine-tuned `aubmindlab/bert-base-arabertv2` for binary end-of-utterance detection | |
| in Saudi Arabic conversational speech. | |
| ## Labels | |
| - 0: Not end of utterance | |
| - 1: End of utterance | |
| ## Intended Use | |
| Real-time conversational agents and turn-taking systems. | |
| ## Example | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification | |
| import torch | |
| tokenizer = AutoTokenizer.from_pretrained("YOUR_USERNAME/arabic-eou-bertv2") | |
| model = AutoModelForSequenceClassification.from_pretrained("YOUR_USERNAME/arabic-eou-bertv2") | |
| inputs = tokenizer("تمام خلاص", return_tensors="pt") | |
| prob = torch.softmax(model(**inputs).logits, dim=-1)[0,1].item() | |