Update app.py

app.py

@@ -1,11 +1,5 @@
 import streamlit as st
-# %%
-Datasets installation
-! pip install datasets transformers
-To install from source instead of the last release, comment the command above and uncomment the following one.
-! pip install git+https://github.com/huggingface/datasets.git
 
-%% [markdown]
 # Quickstart
 
 %% [markdown]
@@ -36,44 +30,7 @@ Check out [Chapter 5](https://huggingface.co/course/chapter5/1?fw=pt) of the Hug
 
 </Tip>
 
-Start by installing 🤗 Datasets:
-
-```bash
-pip install datasets
-```
-
-🤗 Datasets also support audio and image data formats:
-
-* To work with audio datasets, install the [Audio](https://huggingface.co/docs/datasets/main/en/package_reference/main_classes#datasets.Audio) feature:
-
-   ```bash
-   pip install datasets[audio]
-   ```
-
-* To work with image datasets, install the [Image](https://huggingface.co/docs/datasets/main/en/package_reference/main_classes#datasets.Image) feature:
-
-   ```bash
-   pip install datasets[vision]
-   ```
 
-Besides 🤗 Datasets, make sure your preferred machine learning framework is installed:
-
-```bash
-pip install torch
-```
-```bash
-pip install tensorflow
-```
-
-%% [markdown]
-## Audio
-
-%% [markdown]
-Audio datasets are loaded just like text datasets. However, an audio dataset is preprocessed a bit differently. Instead of a tokenizer, you'll need a [feature extractor](https://huggingface.co/docs/transformers/main_classes/feature_extractor#feature-extractor). An audio input may also require resampling its sampling rate to match the sampling rate of the pretrained model you're using. In this quickstart, you'll prepare the [MInDS-14](https://huggingface.co/datasets/PolyAI/minds14) dataset for a model train on and classify the banking issue a customer is having.
-
-**1**. Load the MInDS-14 dataset by providing the [load_dataset()](https://huggingface.co/docs/datasets/main/en/package_reference/loading_methods#datasets.load_dataset) function with the dataset name, dataset configuration (not all datasets will have a configuration), and a dataset split:
-
-# %%
 from datasets import load_dataset, Audio
 
 dataset = load_dataset("PolyAI/minds14", "en-US", split="train", trust_remote_code=True)