Update README.md

README.md

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 # Gradiome / Gradio
 
-Gradio is a python library that allows you to place input and output interfaces over trained models to make it easy for you to "play around" with your model. Gradio runs entirely locally using your browser.
+`Gradio` is a python library that allows you to place input and output interfaces over trained models to make it easy for you to "play around" with your model. Gradio runs entirely locally using your browser.
 
-To get started understanding gradio, I recommend you go in the following order:
-1. Run the Usage.ipynb python notebook
-2. Look at the gradio.py code
-3. Look at the templates/draw_a_digit.html 
+To get a sense of `gradio`, take a look at the  python notebooks in the `examples` folder, or read on below!
 
-You'll notice that gradio includes both front-end design (in the HTML folder) as well as back-end design (gradio.py). 
+## Installation
+```
+pip install gradio
+```
+(you may need to replace `pip` with `pip3` if you're running `python3`).
+
+## Usage
+
+Gradio is super simple to use. The general way it works is something liek this:
+
+
+```
+import tensorflow as tf
+import gradio
+
+mdl = tf.keras.models.Sequential()
+# ... define and train the model as you would normally
+
+iface = gradio.Interface(input=“sketchpad”,
+	output=“class”, model_type=“keras”, model=mdl)
+iface.launch()
+```
+
+Changing the `input` and `output` parameters in the `Interface` face object allow you to create different interfaces, depending on the needs of your model. Take a look at the python notebooks for more examples. The currently supported interfaces are as follows:
+
+**Input interfaces**:
+* Sketchpad
+* ImageUplaod
+* Webcam
+* Textbox
+
+**Output interfaces**:
+* Class
+* Textbox
+
+## Screenshots
+
+
+Here