Update app.py

app.py

@@ -4,14 +4,14 @@ import torch
 import gradio as gr
 labels = ['sadness', 'joy','love', 'anger','fear', 'surprise']
 
-device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+#device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 model_name = "abdulmatinomotoso/emotion_detection_finetuned_distilbert"
-model = AutoModelForSequenceClassification.from_pretrained(model_name).to(device)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 
 def get_emotion(text):
-  input_tensor = tokenizer.encode(text, return_tensors="pt").to("cuda")
+  input_tensor = tokenizer.encode(text, return_tensors="pt")
   logits = model(input_tensor).logits
 
   softmax = torch.nn.Softmax(dim=1)