Instructions to use fkHug/modelFromWav2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fkHug/modelFromWav2vec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="fkHug/modelFromWav2vec")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("fkHug/modelFromWav2vec") model = AutoModelForCTC.from_pretrained("fkHug/modelFromWav2vec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update from
Browse files
config.json → models/config.json
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preprocessor_config.json → models/preprocessor_config.json
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pytorch_model.bin → models/pytorch_model.bin
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scheduler.pt → models/scheduler.pt
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trainer_state.json → models/trainer_state.json
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training_args.bin → models/training_args.bin
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