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("UVA-MSBA/Mod4_T7")
model = AutoModelForSequenceClassification.from_pretrained("UVA-MSBA/Mod4_T7")
def adr_predict(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]
sentence = "I have severe pain."
adr_predict(sentence)