Upload app.py

app.py

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+# import gradio as gr
+
+# demo = gr.load("AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat", src="models")
+
+# demo.launch()
+
+###########################33
+
+import gradio as gr
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+pipe = pipeline("image-classification", model="AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat")
+# Use a pipeline as a high-level helper
+# Load model directly
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+
+processor = AutoImageProcessor.from_pretrained("AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat")
+model = AutoModelForImageClassification.from_pretrained("AZIIIIIIIIZ/vit-base-patch16-224-finetuned-eurosat")
+
+def predict(image):
+  return pipe(image)
+
+demo = gr.Interface(
+  fn=predict,
+  inputs='image',
+  outputs='text',
+)
+
+demo.launch()
+
+# $ pip install gradio_client fastapi uvicorn
+
+
+
+