Instructions to use aadel4/Wav2vec_Classroom_FT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aadel4/Wav2vec_Classroom_FT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="aadel4/Wav2vec_Classroom_FT")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("aadel4/Wav2vec_Classroom_FT") model = AutoModelForCTC.from_pretrained("aadel4/Wav2vec_Classroom_FT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
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