Instructions to use scasutt/wav2vec2-large-xlsr-53_toy_train_data_masked_audio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scasutt/wav2vec2-large-xlsr-53_toy_train_data_masked_audio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="scasutt/wav2vec2-large-xlsr-53_toy_train_data_masked_audio", device_map="auto")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("scasutt/wav2vec2-large-xlsr-53_toy_train_data_masked_audio") model = AutoModelForCTC.from_pretrained("scasutt/wav2vec2-large-xlsr-53_toy_train_data_masked_audio", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 3 years ago
by
SFconvertbot