README.md

import torch import tensorflow as tf from transformers import RobertaTokenizer, RobertaModel from transformers import AutoModelForSequenceClassification from transformers import TFAutoModelForSequenceClassification from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")

tokenizer = AutoTokenizer.from_pretrained("paragon-analytics/bert_empathy") model = AutoModelForSequenceClassification.from_pretrained("paragon-analytics/bert_empathy")

def roberta(x): encoded_input = tokenizer(x, return_tensors='pt') output = model(**encoded_input) scores = output[0][0].detach().numpy() scores = tf.nn.softmax(scores) return scores.numpy()[1]