Instructions to use Alvenir/wav2vec2-base-da-ft-nst with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alvenir/wav2vec2-base-da-ft-nst with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Alvenir/wav2vec2-base-da-ft-nst")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Alvenir/wav2vec2-base-da-ft-nst") model = AutoModelForCTC.from_pretrained("Alvenir/wav2vec2-base-da-ft-nst", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7e0586cc27e1a7dbecfe47c84dbcdb9fea877e2fdfaf9c9a5dcec2d681d8f23
- Size of remote file:
- 378 MB
- SHA256:
- bb6481ad756018c39967395744332907b222fa0847f066b03773341d23dbae7f
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