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minhtoan
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t5-translate-vietnamese-lao

Translation
Transformers
PyTorch
Vietnamese
Lao
mt5
text2text-generation
Inference Endpoints
Model card Files Community
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Update README.md

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@@ -25,8 +25,8 @@ Our work represents a significant advancement in the field of machine translatio
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  ### On GPU
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  ```python
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  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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- tokenizer = AutoTokenizer.from_pretrained("minhtoan/t5-translate-lao-vietnamese")
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- model = AutoModelForSeq2SeqLM.from_pretrained("minhtoan/t5-translate-lao-vietnamese")
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  model.cuda()
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  src = "Tôi muốn mua một cuốn sách"
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  tokenized_text = tokenizer.encode(src, return_tensors="pt").cuda()
@@ -40,8 +40,8 @@ output
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  ### On CPU
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  ```python
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  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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- tokenizer = AutoTokenizer.from_pretrained("minhtoan/t5-translate-lao-vietnamese")
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- model = AutoModelForSeq2SeqLM.from_pretrained("minhtoan/t5-translate-lao-vietnamese")
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  src = "Tôi muốn mua một cuốn sách"
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  input_ids = tokenizer(src, max_length=200, return_tensors="pt", padding="max_length", truncation=True).input_ids
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  outputs = model.generate(input_ids=input_ids, max_new_tokens=200)
 
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  ### On GPU
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  ```python
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  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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+ tokenizer = AutoTokenizer.from_pretrained("minhtoan/t5-translate-vietnamese-lao")
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+ model = AutoModelForSeq2SeqLM.from_pretrained("minhtoan/t5-translate-vietnamese-lao")
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  model.cuda()
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  src = "Tôi muốn mua một cuốn sách"
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  tokenized_text = tokenizer.encode(src, return_tensors="pt").cuda()
 
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  ### On CPU
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  ```python
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  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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+ tokenizer = AutoTokenizer.from_pretrained("minhtoan/t5-translate-vietnamese-lao")
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+ model = AutoModelForSeq2SeqLM.from_pretrained("minhtoan/t5-translate-vietnamese-lao")
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  src = "Tôi muốn mua một cuốn sách"
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  input_ids = tokenizer(src, max_length=200, return_tensors="pt", padding="max_length", truncation=True).input_ids
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  outputs = model.generate(input_ids=input_ids, max_new_tokens=200)