app.py

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

# 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 predict(text):
    probs = expit(model(**tokenizer([text], return_tensors="pt", padding=True)).logits.detach().numpy())
    d = {i: float(np.round(j, 2)) for i, j in zip(all_label_names, probs[0])}
    print(d)
    return d

iface = gr.Interface(
  fn=predict, 
  inputs="text",
  outputs="label",
  #examples=["This test tomorrow is really freaking me out."]
)

iface.launch()