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#import asyncio
#import gc
#import logging
import os
import pandas as pd
#import psutil
import streamlit as st
#from PIL import Image
from streamlit import components
#from streamlit.caching import clear_cache
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from transformers_interpret import SequenceClassificationExplainer
#os.environ["TOKENIZERS_PARALLELISM"] = "false"
#logging.basicConfig(
# format="%(asctime)s : %(levelname)s : %(message)s", level=logging.INFO
#)
#def print_memory_usage():
# logging.info(f"RAM memory % used: {psutil.virtual_memory()[2]}")
@st.cache(allow_output_mutation=True, suppress_st_warning=True, max_entries=1)
def load_model(model_name):
return (
AutoModelForSequenceClassification.from_pretrained(model_name),
AutoTokenizer.from_pretrained(model_name),
)
print ("before main")
st.title("Transformers Interpet Demo App")
print ("end of total file") |