from transformers import BartForConditionalGeneration, AutoTokenizer

model_name = "YOUR_USERNAME/bartpho-vietnamese-summarization"
# Use AutoTokenizer for BARTpho (automatically loads BartphoTokenizer)
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = BartForConditionalGeneration.from_pretrained(model_name)

# Example usage
text = "Your Vietnamese news article text here..."
inputs = tokenizer(text, return_tensors="pt", max_length=1024, truncation=True)
summary_ids = model.generate(inputs["input_ids"], max_length=128, num_beams=4, early_stopping=True)
summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
print(summary)

Training Details

Training Framework: Hugging Face Transformers
GPU: NVIDIA P100 16GB
Batch Size: 8 per device
Gradient Accumulation: 2 steps
Learning Rate: 2e-5
Epochs: 3

htNghiaaa/bartpho-vietnamese-article-summarization

BARTpho Vietnamese Summarization Model

Model Details

Usage

Training Details

htNghiaaa/
bartpho-vietnamese-article-summarization