Add application file

app.py

@@ -1,12 +1,11 @@
 from fastapi import FastAPI
-from transformers import AutoTokenizer
-from optimum.onnxruntime import ORTModelForSequenceClassification
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
 import time
 
-# Load the tokenizer and optimized model
+# Load the tokenizer and model directly
 tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
-model = ORTModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment", from_transformers=True)
+model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
 
 app = FastAPI()
 
@@ -65,6 +64,4 @@ def analyze_sentiment(tweet: str):
         "label": highest_label,
         "score": highest_score,
         "inference_time": round(inference_time, 4)  # In seconds
-    }
-
-
+    }