from transformers import AutoTokenizer, AutoModelForSequenceClassification
from scipy.special import expit
import numpy as np
import os

# set up model
auth_token = os.environ.get("TOKEN") or True
tokenizer = AutoTokenizer.from_pretrained("guidecare/feelings_and_issues", use_auth_token=auth_token )
model = AutoModelForSequenceClassification.from_pretrained("guidecare/feelings_and_issues", use_auth_token=auth_token )
all_label_names = list(model.config.id2label.values())


def probs(text):
    probs = expit(model(**tokenizer([texts], return_tensors="pt", padding=True)).logits.detach().numpy())
    return list(zip(all_label_names, probs[0]))

iface = gr.Interface(
  fn=predict, 
  inputs='What is going on with you',
  outputs='Our predictions',
  examples=[["This test tomorrow is really freaking me out."]]
)

iface.launch()