readme: ---
  license: "mit"
  ---
  
  This is a fine-tuned RoBERTa model that takes text (up to a few sentences) and predicts to what extent it contains empathic language. 
  
  Example classification:
  
  ```python
  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("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]
  
  ```