Update Urbix

Urbix

@@ -200,4 +200,34 @@ demo = gr.Interface(
 if __name__ == "__main__":
     demo.launch(share=True) # The 'share=True' gives you a link you can send to anyone!
 Running on public URL: https://9f191404536439da27.gradio.live
-https://huggingface.co/UrbixAI/Urbix/resolve/main/.gitattributes
+https://huggingface.co/UrbixAI/Urbix/resolve/main/.gitattributes
+# Save after training
+model.save("urbix_model.h5")
+
+# Load in app.py
+model = tf.keras.models.load_model("urbix_model.h5")
+# Change the Interface outputs
+outputs = gr.Label(num_top_classes=2)
+
+# In urbix_analyze, return a dict of probabilities
+return {class_names[0]: float(predictions[0][0]), class_names[1]: float(predictions[0][1])}
+requirements.txt
+This directory includes a few sample datasets to get you started.
+
+*   `california_housing_data*.csv` is California housing data from the 1990 US
+    Census; more information is available at:
+    https://docs.google.com/document/d/e/2PACX-1vRhYtsvc5eOR2FWNCwaBiKL6suIOrxJig8LcSBbmCbyYsayia_DvPOOBlXZ4CAlQ5nlDD8kTaIDRwrN/pub
+
+*   `mnist_*.csv` is a small sample of the
+    [MNIST database](https://en.wikipedia.org/wiki/MNIST_database), which is
+    described at: http://yann.lecun.com/exdb/mnist/
+
+*   `anscombe.json` contains a copy of
+    [Anscombe's quartet](https://en.wikipedia.org/wiki/Anscombe%27s_quartet); it
+    was originally described in
+
+    Anscombe, F. J. (1973). 'Graphs in Statistical Analysis'. American
+    Statistician. 27 (1): 17-21. JSTOR 2682899.
+
+    and our copy was prepared by the
+    [vega_datasets library](https://github.com/altair-viz/vega_datasets/blob/4f67bdaad10f45e3549984e17e1b3088c731503d/vega_datasets/_data/anscombe.json).