Add application file

app.py

@@ -1,13 +1,24 @@
 from fastapi import FastAPI
+<<<<<<< HEAD
 import onnxruntime as ort
 from transformers import AutoTokenizer
+=======
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+>>>>>>> 86f452461e3f04611f1ee50ade207b1a64893e79
 import time
 import torch
 
+<<<<<<< HEAD
 # Load the tokenizer and ONNX model
 tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
 onnx_model_path = "D:/demodeploy/sentiment_model.onnx"
 onnx_session = ort.InferenceSession(onnx_model_path)
+=======
+# Load the tokenizer and model directly
+tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
+model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
+>>>>>>> 86f452461e3f04611f1ee50ade207b1a64893e79
 
 app = FastAPI()
 
@@ -72,4 +83,8 @@ def analyze_sentiment(tweet: str):
         "label": highest_label,
         "score": highest_score,
         "inference_time": round(inference_time, 4)  # In seconds
+<<<<<<< HEAD
+    }
+=======
     }
+>>>>>>> 86f452461e3f04611f1ee50ade207b1a64893e79