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Update README.md

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@@ -12,13 +12,13 @@ inference:
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  max_length: 64
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  widget:
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  - text: >-
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- Learn to build generative AI applications with an expert AWS instructor with the 2-day Developing Generative AI Applications on AWS course.
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  example_title: AWS course
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  - text: >-
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- In healthcare, Generative AI can help generate synthetic medical data to train machine learning models, develop new drug candidates, and design clinical trials.
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  example_title: Generative AI
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  - text: >-
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- By leveraging prior model training through transfer learning, fine-tuning
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  can reduce the amount of expensive computing power and labeled data needed
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  to obtain large models tailored to niche use cases and business needs.
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  example_title: Fine Tuning
@@ -52,7 +52,7 @@ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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  tokenizer = AutoTokenizer.from_pretrained("Ateeqq/Text-Rewriter-Paraphraser", token='YOUR_TOKEN')
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  model = AutoModelForSeq2SeqLM.from_pretrained("Ateeqq/Text-Rewriter-Paraphraser", token='YOUR_TOKEN')
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- text = "Data science is a field that deals with extracting knowledge and insights from data. "
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  inputs = tokenizer(text, return_tensors="pt")
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  max_length: 64
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+ paraphraser: Learn to build generative AI applications with an expert AWS instructor with the 2-day Developing Generative AI Applications on AWS course.
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  example_title: AWS course
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  - text: >-
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+ paraphraser: In healthcare, Generative AI can help generate synthetic medical data to train machine learning models, develop new drug candidates, and design clinical trials.
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  example_title: Generative AI
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  - text: >-
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+ paraphraser: By leveraging prior model training through transfer learning, fine-tuning
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  can reduce the amount of expensive computing power and labeled data needed
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  to obtain large models tailored to niche use cases and business needs.
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  example_title: Fine Tuning
 
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  tokenizer = AutoTokenizer.from_pretrained("Ateeqq/Text-Rewriter-Paraphraser", token='YOUR_TOKEN')
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  model = AutoModelForSeq2SeqLM.from_pretrained("Ateeqq/Text-Rewriter-Paraphraser", token='YOUR_TOKEN')
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+ text = "paraphraser:" + "Data science is a field that deals with extracting knowledge and insights from data. "
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  inputs = tokenizer(text, return_tensors="pt")
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