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@@ -17,23 +17,21 @@ This model is based on the Facebook BART (Bidirectional and Auto-Regressive Tran
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  - **Fine-tuning dataset**: [xsum]
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  ### Inference
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-
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  ```bash
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-
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  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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  tokenizer = AutoTokenizer.from_pretrained("suriya7/text_summarize")
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  model = AutoModelForSeq2SeqLM.from_pretrained("suriya7/text_summarize")
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-
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  def generate_summary(text):
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-
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  inputs = tokenizer([text], max_length=1024, return_tensors='pt', truncation=True)
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-
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  summary_ids = model.generate(inputs['input_ids'],max_new_tokens=100, do_sample=False)
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-
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  summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
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  return summary
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-
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  text_to_summarize = "Now, there is no doubt that one of the most important aspects of any Pixel phone is its camera.
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  And there might be good news for all camera lovers. Rumours have suggested that the Pixel 9 could come with a telephoto lens,
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  improving its photography capabilities even further. Google will likely continue to focus on using AI to
 
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  - **Fine-tuning dataset**: [xsum]
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  ### Inference
 
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  ```bash
 
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  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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  tokenizer = AutoTokenizer.from_pretrained("suriya7/text_summarize")
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  model = AutoModelForSeq2SeqLM.from_pretrained("suriya7/text_summarize")
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+
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  def generate_summary(text):
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+
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  inputs = tokenizer([text], max_length=1024, return_tensors='pt', truncation=True)
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+
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  summary_ids = model.generate(inputs['input_ids'],max_new_tokens=100, do_sample=False)
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+
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  summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
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  return summary
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+
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  text_to_summarize = "Now, there is no doubt that one of the most important aspects of any Pixel phone is its camera.
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  And there might be good news for all camera lovers. Rumours have suggested that the Pixel 9 could come with a telephoto lens,
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  improving its photography capabilities even further. Google will likely continue to focus on using AI to