first commit-> push bear classifier model

app.py

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+import gradio as gr
+from fastai.vision.all import *
+
+# Load the model
+learn = load_learner('export.pkl')
+labels = learn.dls.vocab
+
+def predict(img):
+    img = PILImage.create(img)
+    pred, pred_idx, probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+# Define the Gradio interface
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label(num_top_classes=3),
+    title="Bear Classifier",
+    description="Upload an image to see if it's a Grizzly, Black, or Teddy bear!"
+)
+
+interface.launch()

export.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2b38ed91103fcdcd31f50c338d5fde42a4978d697ba153ce1d4736ea8d714a04
+size 46964571

requirements.txt

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+fastai
+gradio
+torch