Update app.py

app.py

@@ -1,4 +1,24 @@
+import torch
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, AutoConfig
+import numpy as np
+from scipy.special import softmax
 import gradio as gr
+torch.cuda.is_available()
+
+model_path = "cardiffnlp/twitter-roberta-base-sentiment-latest"
+
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+config = AutoConfig.from_pretrained(model_path)
+model = AutoModelForSequenceClassification.from_pretrained(model_path)
+
+def sentiment_analysis(text):
+    encoded_input = tokenizer(text, return_tensors='pt')
+    output = model(**encoded_input)
+    scores_ = output[0][0].detach().numpy()
+    scores_ = softmax(scores_)
+    labels = ['Negative', 'Neutral', 'Positive']
+    scores = {l: float(s) for (l, s) in zip(labels, scores_)}
+    return scores
 
 demo = gr.Interface(
     theme=gr.themes.Base(),