Instructions to use scasutt/wav2vec2-base_toy_train_data_random_low_pass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scasutt/wav2vec2-base_toy_train_data_random_low_pass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="scasutt/wav2vec2-base_toy_train_data_random_low_pass")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("scasutt/wav2vec2-base_toy_train_data_random_low_pass") model = AutoModelForCTC.from_pretrained("scasutt/wav2vec2-base_toy_train_data_random_low_pass", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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