Update app.py

app.py

@@ -1,14 +1,14 @@
 import gradio as gr
-import torch
 import requests
 from PIL import Image
 from transformers import BlipProcessor, BlipForConditionalGeneration
 
+
 processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
-model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base", torch_dtype=torch.float16).to("cuda")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
 
 def execute(image): 
-    inputs = processor(raw_image, return_tensors="pt").to("cuda", torch.float16)
+    inputs = processor(raw_image, return_tensors="pt")
     out = model.generate(**inputs)
     output = processor.decode(out[0], skip_special_tokens=True)
     return output