Instructions to use rkmt/wav2vec2-base-timit-demo-colab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rkmt/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="rkmt/wav2vec2-base-timit-demo-colab")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rkmt/wav2vec2-base-timit-demo-colab") model = AutoModelForCTC.from_pretrained("rkmt/wav2vec2-base-timit-demo-colab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 9500
Browse files
pytorch_model.bin
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runs/Dec29_12-57-55_rkmtk2/events.out.tfevents.1640750517.rkmtk2.194273.2
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