Instructions to use patrickvonplaten/wav2vec2-base-timit-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patrickvonplaten/wav2vec2-base-timit-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="patrickvonplaten/wav2vec2-base-timit-demo")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("patrickvonplaten/wav2vec2-base-timit-demo") model = AutoModelForCTC.from_pretrained("patrickvonplaten/wav2vec2-base-timit-demo") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
Wav2Vec2 Fine-Tuned on English dataset Timit
The model was fine-tuned in a google colab for demonstration purposes. Please refer to this blog for more information about the model.
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