import streamlit as st 
from transformers import pipeline
from transformers import AutoTokenizer
from datasets import load_dataset


tokenizer = AutoTokenizer.from_pretrained('bert-base-cased')
dataset = load_dataset("Balaji576/car_diagnostics", split="train")
encoded_dataset = dataset.map(lambda examples: tokenizer(examples['text']), batched=True)
encoded_dataset.column_names

pipe = pipeline("sentiment-analysis")
text = st.text_area('enter some text!')

if text:
    out = pipe(text)
    st.json(out)