Upload app.py

app.py

@@ -1,3 +1,16 @@
 import gradio as gr
 
-gr.load("models/umm-maybe/blip-image-captioning-base-finetuned").launch()
+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")
+
+def caption_image(raw_image):
+    inputs = processor(raw_image, return_tensors="pt")
+    out = model.generate(**inputs)
+    return processor.decode(out[0], skip_special_tokens=True)
+
+demo = gr.Interface(fn=caption_image, inputs="image", outputs="caption")
+demo.launch()