Instructions to use facebook/data2vec-audio-large-100h with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/data2vec-audio-large-100h with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/data2vec-audio-large-100h")# Load model directly from transformers import AutoTokenizer, AutoModelForCTC tokenizer = AutoTokenizer.from_pretrained("facebook/data2vec-audio-large-100h") model = AutoModelForCTC.from_pretrained("facebook/data2vec-audio-large-100h", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 559e07c467adc16d8c22d64d1e4ba43c7f176c71e16c67fc58e47d38dbb9f046
- Size of remote file:
- 1.25 GB
- SHA256:
- efb83688af9d180cf9c3817f6525c81cbb54e8566580d3b1e9b92bb5d176921d
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