File size: 1,044 Bytes
587a46c 9dd5641 587a46c 9dd5641 587a46c b5a954c 587a46c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 |
import streamlit as st
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch.nn.functional as F
# Load tokenizer and model
model_ckpt = "AbhishekBhavnani/TweetClassification"
tokenizer = AutoTokenizer.from_pretrained(model_ckpt)
model = AutoModelForSequenceClassification.from_pretrained(model_ckpt)
model.eval() # Important for inference mode
# App UI
st.title("Tweet Emotion Classifier")
text = st.text_area("Enter your tweet here")
if st.button("Predict"):
if text.strip():
with torch.no_grad():
# Tokenize input
inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
outputs = model(**inputs)
probs = F.softmax(outputs.logits, dim=-1)
top = torch.argmax(probs, dim=1).item()
label = model.config.id2label[top]
score = probs[0][top].item()
st.success(f"**Prediction**: {label} ({score:.4f})")
else:
st.warning("Please enter a tweet.")
|