Update README.md

README.md

@@ -24,8 +24,8 @@ With a commitment to quality and innovation, our translation model not only tran
 ### On GPU
 ```python
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-tokenizer = AutoTokenizer.from_pretrained("minhtoan/t5-translation-lao-english")  
-model = AutoModelForSeq2SeqLM.from_pretrained("minhtoan/t5-translation-lao-english")
+tokenizer = AutoTokenizer.from_pretrained("minhtoan/t5-translate-lao-english")  
+model = AutoModelForSeq2SeqLM.from_pretrained("minhtoan/t5-translate-lao-english")
 model.cuda()
 src = "ຂ້ອຍ​ຮັກ​ເຈົ້າ"
 tokenized_text = tokenizer.encode(src, return_tensors="pt").cuda()
@@ -39,8 +39,8 @@ output
 ### On CPU
 ```python
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-tokenizer = AutoTokenizer.from_pretrained("minhtoan/t5-translation-lao-english")  
-model = AutoModelForSeq2SeqLM.from_pretrained("minhtoan/t5-translation-lao-english")
+tokenizer = AutoTokenizer.from_pretrained("minhtoan/t5-translate-lao-english")  
+model = AutoModelForSeq2SeqLM.from_pretrained("minhtoan/t5-translate-lao-english")
 src = "ຂ້ອຍ​ຮັກ​ເຈົ້າ"
 input_ids = tokenizer(src, max_length=200, return_tensors="pt", padding="max_length", truncation=True).input_ids
 outputs = model.generate(input_ids=input_ids, max_new_tokens=140)