Instructions to use facebook/data2vec-audio-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/data2vec-audio-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/data2vec-audio-large")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("facebook/data2vec-audio-large") model = AutoModel.from_pretrained("facebook/data2vec-audio-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78b5166a9961c773e9adda3f4ac56ec2479d39fe992f3420e59b4de953670ef5
- Size of remote file:
- 1.25 GB
- SHA256:
- 37d1142e23882cec689552e3251c30128dc9620cae13c8c5cf89f6e976eb9019
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.