Update app.py

app.py

@@ -0,0 +1,23 @@
+import torch
+from transformers import AutoProcessor,AutoModelForCausalLM
+import gradio as gr 
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+processor=AutoProcessor.from_pretrained("saravanamax/General_image_captioning")
+model=AutoModelForCausalLM.from_pretrained("saravanamax/General_image_captioning").to(device)
+def generate_caption(image):
+  encoded=processor(images=image, return_tensors="pt").to(device)
+  pixels=encoded['pixel_values'].to(device)
+  with torch.no_grad():
+    generated_ids=model.generate(pixel_values=pixels,max_length=10)
+  generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+  return generated_caption 
+demo=gr.Interface(
+    fn=generate_caption,
+    inputs=[
+        gr.Image(type='pil'),
+    ],
+    outputs= 'label',
+    examples=['sample.jpg','sample1.jpg','sample2.jpg'],
+      theme=gr.themes.Soft(primary_hue='purple',secondary_hue=gr.themes.colors.gray)
+)
+demo.launch(show_error=True)