Updated README.md with pipeline example
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by
yj2773
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README.md
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@@ -38,6 +38,29 @@ This model is based on the T5-base model. We used "transfer learning" to get our
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[Author's LinkedIn](https://www.linkedin.com/in/vladimir-vorobev/) link
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## Deploying example
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```python
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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[Author's LinkedIn](https://www.linkedin.com/in/vladimir-vorobev/) link
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## Using with pipeline
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```python
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from transformers import pipeline
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generator = pipeline(model="humarin/chatgpt_paraphraser_on_T5_base")
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```
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**Input**
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```python
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generator('What are the best places to see in New York?', num_return_sequences=5, do_sample=True)
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```
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**Output**
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```python
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[{'generated_text': 'Which locations in New York are worth visiting and why?'},
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{'generated_text': 'Can you recommend any must-see sites in New York?'},
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{'generated_text': 'Which Bostonian sites are considered the funniest to visit in New York?'},
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{'generated_text': 'Which are the top destinations to discover in New York?'},
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{'generated_text': 'What are some must-see attractions in New York?'}]
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```
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You may also construct the pipeline from the loaded model and tokenizer yourself and consider the preprocessing steps:
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## Deploying example
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```python
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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