Instructions to use Pinwheel/wav2vec2-base-timit-demo-colab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pinwheel/wav2vec2-base-timit-demo-colab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Pinwheel/wav2vec2-base-timit-demo-colab")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Pinwheel/wav2vec2-base-timit-demo-colab") model = AutoModelForCTC.from_pretrained("Pinwheel/wav2vec2-base-timit-demo-colab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b83da3679f9b841486a153af8ac0f06c2a7bf74716f7d260f63f6d619c6d42b5
- Size of remote file:
- 2.86 kB
- SHA256:
- cac1b402efc1ba10badc5571beb4d1e74521dd565d4da3122f9742a66fa07a6d
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