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Update README.md

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@@ -24,11 +24,12 @@ This repository contains the finetuned mT5-base model for Thai sentence summariz
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  ### Example
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  ```python
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  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
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  tokenizer = AutoTokenizer.from_pretrained("preechanon/mt5-base-thaisum-text-summarization")
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  model = AutoModelForSeq2SeqLM.from_pretrained("preechanon/mt5-base-thaisum-text-summarization")
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- new_input_string = "ข้อความที่ต้องการสรุป"
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- input_ =tokenizer(new_input_string, truncation=True, max_length=1024, return_tensors="pt")
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  with torch.no_grad():
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  preds = model.generate(
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  input_['input_ids'].to('cpu'),
@@ -38,6 +39,9 @@ with torch.no_grad():
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  remove_invalid_values=True,
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  max_length=140,
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  )
 
 
 
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  ```
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  ### Score
 
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  ### Example
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  ```python
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  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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+ import torch
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  tokenizer = AutoTokenizer.from_pretrained("preechanon/mt5-base-thaisum-text-summarization")
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  model = AutoModelForSeq2SeqLM.from_pretrained("preechanon/mt5-base-thaisum-text-summarization")
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+ new_input_string = "ข้อความที่ต้องการ"
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+ input_ = tokenizer(new_input_string, truncation=True, max_length=1024, return_tensors="pt")
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  with torch.no_grad():
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  preds = model.generate(
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  input_['input_ids'].to('cpu'),
 
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  remove_invalid_values=True,
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  max_length=140,
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  )
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+
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+ summary = tokenizer.decode(preds[0], skip_special_tokens=True)
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+ summary
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  ```
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  ### Score