Instructions to use facebook/musicgen-stereo-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/musicgen-stereo-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="facebook/musicgen-stereo-small")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/musicgen-stereo-small") model = AutoModelForTextToWaveform.from_pretrained("facebook/musicgen-stereo-small") - Audiocraft
How to use facebook/musicgen-stereo-small with Audiocraft:
from audiocraft.models import MusicGen model = MusicGen.get_pretrained("facebook/musicgen-stereo-small") descriptions = ['happy rock', 'energetic EDM', 'sad jazz'] wav = model.generate(descriptions) # generates 3 samples. - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76e582da68f502caae677d7637f56b1dbb959c729d97354c8527f38f608df98b
- Size of remote file:
- 2.43 GB
- SHA256:
- dbca44512d9e1dc0399a25706c882f5dc280dfeafe61dbe8278b9d396e3754bd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.