Instructions to use Raffay/speech_processing_project_wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raffay/speech_processing_project_wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Raffay/speech_processing_project_wav2vec2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Raffay/speech_processing_project_wav2vec2") model = AutoModelForCTC.from_pretrained("Raffay/speech_processing_project_wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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update model card README.md
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End of training
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update model card README.md
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add tokenizer
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initial commit
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