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Update README.md

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@@ -32,7 +32,9 @@ counter false health information on their sites. In July, US PresidentJoe Biden
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  people's scepticism in getting vaccinated by spreading misinformation, and appealed for them to address the issue. YouTube, which is owned
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  by Google, said 130,000 videos were removed from its platform since last year, when it implemented a ban on content spreading misinformation
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  about Covid vaccines. In a blog post, the company said it had seen false claims about Covid jabs "spill over into misinformation about
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- vaccines in general". The new policy covers long-approved vaccines, such as those against measles or hepatitis B."We're expanding our medical misinformation policies on YouTube with new guidelines on currently administered vaccines that are approved and confirmed to be safe and effective by local health authorities and the WHO," the post said, referring to the World Health Organization.
 
 
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  """
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  inputs = tokenizer.encode("summarize: " + article, return_tensors="pt", max_length=512, truncation=True)
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  summary_ids = model.generate(inputs, max_length=150, min_length=50, length_penalty=2.0, num_beams=4, early_stopping=True)
 
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  people's scepticism in getting vaccinated by spreading misinformation, and appealed for them to address the issue. YouTube, which is owned
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  by Google, said 130,000 videos were removed from its platform since last year, when it implemented a ban on content spreading misinformation
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  about Covid vaccines. In a blog post, the company said it had seen false claims about Covid jabs "spill over into misinformation about
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+ vaccines in general". The new policy covers long-approved vaccines, such as those against measles or hepatitis B."We're expanding our medical
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+ misinformation policies on YouTube with new guidelines on currently administered vaccines that are approved and confirmed to be safe and
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+ effective by local health authorities and the WHO," the post said, referring to the World Health Organization.
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  """
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  inputs = tokenizer.encode("summarize: " + article, return_tensors="pt", max_length=512, truncation=True)
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  summary_ids = model.generate(inputs, max_length=150, min_length=50, length_penalty=2.0, num_beams=4, early_stopping=True)