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Create README.md

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+ import torch
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+ import tensorflow as tf
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+ from transformers import RobertaTokenizer, RobertaModel
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+ from transformers import AutoModelForSequenceClassification
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+ from transformers import TFAutoModelForSequenceClassification
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+ from transformers import AutoTokenizer
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+ # tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
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+ tokenizer = AutoTokenizer.from_pretrained("paragon-analytics/bert_empathy")
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+ model = AutoModelForSequenceClassification.from_pretrained("paragon-analytics/bert_empathy")
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+
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+ def roberta(x):
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+ encoded_input = tokenizer(x, return_tensors='pt')
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+ output = model(**encoded_input)
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+ scores = output[0][0].detach().numpy()
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+ scores = tf.nn.softmax(scores)
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+ return scores.numpy()[1]