Create README.md

README.md

@@ -0,0 +1,48 @@
+---
+language:
+- vi
+
+tags:
+- t5
+- seq2seq
+
+# Machine translation for vietnamese
+## Model Description
+T5-vi-en-base is a transformer model for vietnamese machine translation designed using T5 architecture.
+## Training data
+T5-vi-en-base was trained on 4M sentence pairs (english,vietnamese)
+### How to use
+
+```py
+from transformers import T5ForConditionalGeneration, T5Tokenizer
+import torch
+if torch.cuda.is_available():       
+    device = torch.device("cuda")
+
+    print('There are %d GPU(s) available.' % torch.cuda.device_count())
+
+    print('We will use the GPU:', torch.cuda.get_device_name(0))
+else:
+    print('No GPU available, using the CPU instead.')
+    device = torch.device("cpu")
+
+model = T5ForConditionalGeneration.from_pretrained("NlpHUST/t5-vi-en-base")
+tokenizer = T5Tokenizer.from_pretrained("NlpHUST/t5-vi-en-base")
+model.to(device)
+
+src = "Theo lãnh đạo Sở Y tế, 3 người này không có triệu chứng sốt, ho, khó thở, đã được lấy mẫu xét nghiệm và cách ly tập trung."
+tokenized_text = tokenizer.encode(src, return_tensors="pt").to(device)
+model.eval()
+summary_ids = model.generate(
+                    tokenized_text,
+                    max_length=256, 
+                    num_beams=5,
+                    repetition_penalty=2.5, 
+                    length_penalty=1.0, 
+                    early_stopping=True
+                )
+output = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+print(output)
+
+According to the head of the Department of Health, the three people had no symptoms of fever, cough, shortness of breath, were taken samples for testing and concentrated quarantine.
+```