Instructions to use GroNLP/wav2vec2-dutch-large-ft-cgn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GroNLP/wav2vec2-dutch-large-ft-cgn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GroNLP/wav2vec2-dutch-large-ft-cgn")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("GroNLP/wav2vec2-dutch-large-ft-cgn") model = AutoModelForCTC.from_pretrained("GroNLP/wav2vec2-dutch-large-ft-cgn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90c65830d059772a083011f71ab599d1bfbac4ac19e47045616b0c097d41ebcc
- Size of remote file:
- 1.26 GB
- SHA256:
- f7671876f738ea93d12d873633240106323b4e7d243f7b2e7afe4b986919d381
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