Instructions to use facebook/encodec_48khz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/encodec_48khz with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/encodec_48khz")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("facebook/encodec_48khz") model = AutoModel.from_pretrained("facebook/encodec_48khz", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/encodec_48khz: direct link, hf CLI and curl.
- Browser
- Download file 76.3 MB
-
https://huggingface.co/facebook/encodec_48khz/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/encodec_48khz/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/encodec_48khz/resolve/main/pytorch_model.bin
76.3 MB
- Xet hash:
- 7fa6870d1224d4d61824549218541208a1cb3f285af352e0d7292e139fa6b816
- Size of remote file:
- 76.3 MB
- SHA256:
- 0a6bd2506e38ec181c7aa65ef8314d7165fe8fac131c213bb1ad9b6ab4505232
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