Create app.py

app.py

@@ -0,0 +1,32 @@
+import streamlit as st 
+import pandas as pd 
+import numpy as np 
+
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline, AutoConfig 
+model_ckpt = "AbhishekBhavnani/TweetClassification" 
+
+model = AutoModelForSequenceClassification.from_pretrained(
+    model_ckpt,
+    low_cpu_mem_usage=True  # To prevent large memory usage during loading
+)
+
+tokenizer = AutoTokenizer.from_pretrained(model_ckpt)
+
+
+# Use the pipeline for text classification
+classifier = pipeline(
+    'text-classification',
+    model=model,
+    tokenizer=tokenizer,
+    device=-1  # -1 for CPU, set to GPU index if available (e.g., device=0)
+) 
+
+st.title("Tweet Classification")
+
+text = st.text_area("Enter Your Tweet Here")  
+
+if st.button("Predict"):  
+    result = classifier(text)
+    st.write(result)   
+
+