Instructions to use webshell/wav2vec2-base-fine-tune-timit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use webshell/wav2vec2-base-fine-tune-timit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="webshell/wav2vec2-base-fine-tune-timit")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("webshell/wav2vec2-base-fine-tune-timit") model = AutoModelForCTC.from_pretrained("webshell/wav2vec2-base-fine-tune-timit") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
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