update Readme

README.md

@@ -23,27 +23,56 @@ It achieves the following results on the evaluation set:
 - Train Loss: 0.1596
 - Validation Loss: 0.2877
 - Epoch: 3
+- Bleu: 77.71982942978268
 
 ## Model description
 
-More information needed
+### 🧪 Quick Start
 
-## Intended uses & limitations
+First, make sure to install the `transformers` library:
+```bash
+pip install transformers
+```
 
-More information needed
 
-## Training and evaluation data
+Option 1: Use a pipeline as a high-level helper
+```python
+from transformers import pipeline
 
-More information needed
+pipe = pipeline("translation", model="trinhhuy/finetuned-opus-mt-en-vi")
+
+result = pipe("I'm confident that my friend will pass the exam because he has been studying hard and staying focused for weeks.")
+print(result)
+```
+```text
+[{'translation_text': 'Tôi tự tin rằng bạn tôi sẽ vượt qua kỳ thi vì anh ấy đã học tập chăm chỉ và tập trung nhiều tuần.'}]
+```
+Option 2: Load model directly
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("trinhhuy/finetuned-opus-mt-en-vi")
+model = AutoModelForSeq2SeqLM.from_pretrained("trinhhuy/finetuned-opus-mt-en-vi")
+
+input_tokenized = tokenizer("I'm confident that my friend will pass the exam because he has been studying hard and staying focused for weeks.", return_tensors="pt")
+output_tokenized = model.generate(**input_tokenized)
+
+translated_text = tokenizer.decode(output_tokenized[0], skip_special_tokens=True)
+print(translated_text)
+```
+```text
+Tôi tự tin rằng bạn tôi sẽ vượt qua kỳ thi vì anh ấy đã học tập chăm chỉ và tập trung nhiều tuần.
+```
 
-## Training procedure
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 25412, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': np.float32(0.9), 'beta_2': np.float32(0.999), 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
+- initial_learning_rate = 5e-05
+- weight_decay_rate = 0.01
 - training_precision: mixed_float16
 
+
 ### Training results
 
 | Train Loss | Validation Loss | Epoch |