Delete app.py with huggingface_hub

app.py

@@ -1,143 +0,0 @@
-# A Blocks implementation of https://erlj.notion.site/Neural-Instrument-Cloning-from-very-few-samples-2cf41d8b630842ee8c7eb55036a1bfd6
-
-import datetime
-import os
-import random
-
-import gradio as gr
-from gradio.components import Markdown as m
-
-
-def get_time():
-    now = datetime.datetime.now()
-    return now.strftime("%m/%d/%Y, %H:%M:%S")
-
-
-def generate_recording():
-    return random.choice(["new-sax-1.mp3", "new-sax-1.wav"])
-
-
-def reconstruct(audio):
-    return random.choice(["new-sax-1.mp3", "new-sax-1.wav"])
-
-
-io1 = gr.Interface(
-    lambda x, y, z: os.path.join(os.path.dirname(__file__),"sax.wav"),
-    [
-        gr.Slider(label="pitch"),
-        gr.Slider(label="loudness"),
-        gr.Audio(label="base audio file (optional)"),
-    ],
-    gr.Audio(),
-)
-
-io2 = gr.Interface(
-    lambda x, y, z: os.path.join(os.path.dirname(__file__),"flute.wav"),
-    [
-        gr.Slider(label="pitch"),
-        gr.Slider(label="loudness"),
-        gr.Audio(label="base audio file (optional)"),
-    ],
-    gr.Audio(),
-)
-
-io3 = gr.Interface(
-    lambda x, y, z: os.path.join(os.path.dirname(__file__),"trombone.wav"),
-    [
-        gr.Slider(label="pitch"),
-        gr.Slider(label="loudness"),
-        gr.Audio(label="base audio file (optional)"),
-    ],
-    gr.Audio(),
-)
-
-io4 = gr.Interface(
-    lambda x, y, z: os.path.join(os.path.dirname(__file__),"sax2.wav"),
-    [
-        gr.Slider(label="pitch"),
-        gr.Slider(label="loudness"),
-        gr.Audio(label="base audio file (optional)"),
-    ],
-    gr.Audio(),
-)
-
-demo = gr.Blocks(title="Neural Instrument Cloning")
-
-with demo.clear():
-    m(
-        """
-    ## Neural Instrument Cloning from Very Few Samples
-    <center><img src="https://media.istockphoto.com/photos/brass-trombone-picture-id490455809?k=20&m=490455809&s=612x612&w=0&h=l9KJvH_25z0QTLggHrcH_MsR4gPLH7uXwDPUAZ_C5zk=" width="400px"></center>"""
-    )
-    m(
-        """
-    This Blocks implementation is an adaptation [a report written](https://erlj.notion.site/Neural-Instrument-Cloning-from-very-few-samples-2cf41d8b630842ee8c7eb55036a1bfd6) by Nicolas Jonason and Bob L.T. Sturm.
-    
-    I've implemented it in Blocks to show off some cool features, such as embedding live ML demos. More on that ahead...
-    
-    ### What does this machine learning model do?
-    It combines techniques from neural voice cloning with musical instrument synthesis. This makes it possible to produce neural instrument synthesisers from just seconds of target instrument audio.
-    
-    ### Audio Examples
-    Here are some **real** 16 second saxophone recordings:
-    """
-    )
-    gr.Audio(os.path.join(os.path.dirname(__file__),"sax.wav"), label="Here is a real 16 second saxophone recording:")
-    gr.Audio(os.path.join(os.path.dirname(__file__),"sax.wav"))
-
-    m(
-        """\n
-        Here is a **generated** saxophone recordings:"""
-    )
-    a = gr.Audio(os.path.join(os.path.dirname(__file__),"new-sax.wav"))
-
-    gr.Button("Generate a new saxophone recording")
-
-    m(
-        """
-    ### Inputs to the model
-    The inputs to the model are:
-    * pitch
-    * loudness
-    * base audio file
-    """
-    )
-
-    m(
-        """
-    Try the model live!
-    """
-    )
-
-    gr.TabbedInterface(
-        [io1, io2, io3, io4], ["Saxophone", "Flute", "Trombone", "Another Saxophone"]
-    )
-
-    m(
-        """
-    ### Using the model for cloning
-    You can also use this model a different way, to simply clone the audio file and reconstruct it 
-    using machine learning. Here, we'll show a demo of that below:
-    """
-    )
-
-    a2 = gr.Audio()
-    a2.change(reconstruct, a2, a2)
-
-    m(
-        """
-    Thanks for reading this! As you may have realized, all of the "models" in this demo are fake. They are just designed to show you what is possible using Blocks 🤗.
-    
-    For details of the model, read the [original report here](https://erlj.notion.site/Neural-Instrument-Cloning-from-very-few-samples-2cf41d8b630842ee8c7eb55036a1bfd6).
-    
-    *Details for nerds*: this report was "launched" on:
-    """
-    )
-
-    t = gr.Textbox(label="timestamp")
-
-    demo.load(get_time, [], t)
-
-
-if __name__ == "__main__":
-    demo.launch()