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app.py

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+import os
+import io
+import IPython.display
+from PIL import Image
+from transformers import pipeline
+import gradio as gr
+
+hf_api_key = os.environ["HF_API_KEY"]
+
+get_completion = pipeline(os.environ["TASK"],model= os.environ["MODEL"])
+
+def summarize(input):
+    output = get_completion(input)
+    return output[0]['generated_text']
+
+def captioner(image):
+    result = get_completion(image)
+    return result[0]['generated_text']
+
+gr.close_all()
+demo = gr.Interface(fn=captioner,
+                    inputs=[gr.Image(label="Upload image", type="pil")],
+                    outputs=[gr.Textbox(label="Caption")],
+                    title="Image Captioning with BLIP",
+                    description="Caption any image using the BLIP model",
+                    allow_flagging="never",
+                    examples=["bridge.jpg", "Sea.jpg", "Umbrella.jpg"])
+                   
+
+demo.launch(share=True)

requirements.txt

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+IPython
+transformers
+gradio