Create application

app.py

@@ -0,0 +1,37 @@
+import gradio as gr
+from huggingface_hub import from_pretrained_fastai
+repo_id = "hugginglearners/flowers_101_convnext_model"
+
+learn = from_pretrained_fastai(repo_id)
+labels = learn.dls.vocab
+
+
+
+def predict(img):
+    img = PILImage.create(img)
+    _pred, _pred_w_idx, probs = learn.predict(img)
+    # gradio doesn't support tensors, so converting to float
+    labels_probs = {labels[i]: float(probs[i]) for i, _ in enumerate(labels)}
+    return labels_probs
+
+interface_options = {
+    "title": "Identify which flower it is?",
+    "description": "It’s difficult to fathom just how vast and diverse our natural world is.There are over 5,000 species of mammals, 10,000 species of birds, 30,000 species of fish – and astonishingly, over 400,000 different types of flowers.\n Identify which flower variety it is by uploading your images of flowers.",
+    "interpretation": "default",
+    "layout": "horizontal",
+    "allow_flagging": "never",
+}
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(192, 192)),
+    outputs=gr.outputs.Label(num_top_classes=3),
+    **interface_options,
+)
+
+launch_options = {
+    "enable_queue": True,
+    "share": True,
+}
+
+demo.launch(**launch_options)