Instructions to use strumber/Meta-AudioGen-API with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use strumber/Meta-AudioGen-API with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("strumber/Meta-AudioGen-API", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download audio_craft_model.py from strumber/Meta-AudioGen-API: direct link, hf CLI and curl.
- Browser
- Download file 638 Bytes
-
https://huggingface.co/strumber/Meta-AudioGen-API/resolve/main/audio_craft_model.py
- Command line
-
hf download hf://strumber/Meta-AudioGen-API/audio_craft_model.py
-
curl -L -o audio_craft_model.py https://huggingface.co/strumber/Meta-AudioGen-API/resolve/main/audio_craft_model.py
638 Bytes
| import torch | |
| from audiocraft.models import AudioGen | |
| from audiocraft.data.audio import audio_write | |
| class AudioCraftGenerator(torch.nn.Module): | |
| def __init__(self, model_name='facebook/audiogen-medium', duration=5): | |
| super(AudioCraftGenerator, self).__init__() | |
| self.model = AudioGen.get_pretrained(model_name) | |
| self.model.set_generation_params(duration=duration) | |
| def forward(self, descriptions): | |
| wav = self.model.generate(descriptions) | |
| return wav | |
| def save_wav(self, wav, idx): | |
| audio_write(f'{idx}', wav.cpu(), self.model.sample_rate, strategy="loudness", loudness_compressor=True) |