Instructions to use flax-community/wav2vec2-spanish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flax-community/wav2vec2-spanish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="flax-community/wav2vec2-spanish")# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("flax-community/wav2vec2-spanish") model = AutoModelForPreTraining.from_pretrained("flax-community/wav2vec2-spanish", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb17328e804091b5799f74a5308a3014f72e63d4943a7cc2004b63125f8f3925
- Size of remote file:
- 191 MB
- SHA256:
- fbbc11afa4c10b6f71b6a3d57eddce5acddbeaf6b6916d844cde44d920321daf
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