Instructions to use facebook/musicgen-stereo-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/musicgen-stereo-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="facebook/musicgen-stereo-medium")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("facebook/musicgen-stereo-medium") model = AutoModelForTextToWaveform.from_pretrained("facebook/musicgen-stereo-medium", device_map="auto") - Audiocraft
How to use facebook/musicgen-stereo-medium with Audiocraft:
from audiocraft.models import MusicGen model = MusicGen.get_pretrained("facebook/musicgen-stereo-medium") descriptions = ['happy rock', 'energetic EDM', 'sad jazz'] wav = model.generate(descriptions) # generates 3 samples. - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/musicgen-stereo-medium: direct link, hf CLI and curl.
- Browser
- Download file 4.07 GB
-
https://huggingface.co/facebook/musicgen-stereo-medium/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/musicgen-stereo-medium/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/musicgen-stereo-medium/resolve/main/pytorch_model.bin
4.07 GB
- Xet hash:
- 4ede243b9573f667a9eef724c627fc5fbf34d74afecf7af66df14a2e5506b1bd
- Size of remote file:
- 4.07 GB
- SHA256:
- dbe579b7b22cc0769e9547396529e7ac5df2defbd806e6491301abe9c6086b23
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