test_audio_clips / README.md
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Upload README.md with huggingface_hub
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---
dataset_info:
features:
- name: audio
dtype: audio
- name: audio_names
dtype: string
- name: class_label
dtype:
class_label:
names:
'0': bad
'1': okay
'2': good
'3': great
splits:
- name: train
num_bytes: 12388426.0
num_examples: 6
download_size: 12391305
dataset_size: 12388426.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
Follow these steps to set up and upload your audio dataset to Hugging Face:
* **Create a Virtual Environment**
- Start by creating a virtual environment on your machine. Run the following commands:
# On Windows
```
python -m venv env
./env/Scripts/activate
```
# On macOS/Linux
```
source env/bin/activate
pip install -r requirements.txt
```
* **Generate a Hugging Face Token**
- To interact with Hugging Face and push datasets, you'll need a Hugging Face access token. Follow these steps to generate one:
- Go to [Hugging Face Settings](https://huggingface.co/settings/tokens).
- Click on "New Token."
- Give the token a name and select the Role as "Write."
- Copy the generated token.
* **Configure Your Token**
- Run the following command, replacing `'YOUR_TOKEN_HERE'` with the token you obtained from Hugging Face:
```bash
python -c "from huggingface_hub.hf_api import HfFolder; HfFolder.save_token('YOUR_TOKEN_HERE')"
```
This command will configure your environment with your Hugging Face token.
* **Modify `main.py`**
- In the `main.py` file, make the following changes:
- Replace `'Enter-Your-hub-name'` with the name of your dataset. For example, use `'AneeqMalik/test_audio_clips'`.
```python
audio_dataset.push_to_hub("Enter-Your-hub-name")
```
This line specifies where your dataset will be pushed on Hugging Face.
* **Run the Code**
- To push your audio dataset to Hugging Face, execute the following command:
```bash
python main.py
```
Your audio dataset will be uploaded to Hugging Face under the specified name.