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# AudioEditingCode Colab Demo
This notebook demonstrates how to use the `AudioEditingCode` repository in Google Colab.
## 1. Clone the repository
```bash
!git clone https://github.com/HilaManor/AudioEditingCode.git
%cd AudioEditingCode
```
## 2. Install dependencies
```bash
!pip install -r requirements.txt
```
## 3. Demo Usage
Here you can add examples of how to use the code. You might need to download some audio files for demonstration.
### Download example audio
```bash
!wget https://www.soundhelix.com/examples/mp3/SoundHelix-Song-1.mp3 -O input_audio.mp3
```
### Text-Based Editing Example
This example uses `main_run.py` for text-based audio editing. You will need a Hugging Face token to use models like Stable Audio Open. Please visit [Hugging Face](https://huggingface.co/settings/tokens) to get your token and replace `<YOUR_HF_TOKEN>` below.
```python
import os
# Replace with your actual Hugging Face token
os.environ["HF_TOKEN"] = "<YOUR_HF_TOKEN>"
!python code/main_run.py \
--cfg_tar 1.5 \
--cfg_src 0.5 \
--init_aud input_audio.mp3 \
--target_prompt "a dog barking" \
--tstart 100 \
--model_id audioldm \
--results_path results_text_based
```
### Unsupervised Editing Example
First, extract the principal components:
```bash
!python code/main_pc_extract_inv.py \
--init_aud input_audio.mp3 \
--model_id audioldm \
--results_path results_unsupervised_extract \
--drift_start 0 \
--drift_end 200 \
--n_evs 5
```
Then, apply the principal components:
```bash
!python code/main_pc_apply_drift.py \
--extraction_path results_unsupervised_extract/input_audio_audioldm_inversion_data.pt \
--drift_start 0 \
--drift_end 200 \
--amount 1.0 \
--evs 0
```
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