Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use rossevine/Model_G_Wav2Vec2_Version3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rossevine/Model_G_Wav2Vec2_Version3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rossevine/Model_G_Wav2Vec2_Version3")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rossevine/Model_G_Wav2Vec2_Version3") model = AutoModelForCTC.from_pretrained("rossevine/Model_G_Wav2Vec2_Version3") - Notebooks
- Google Colab
- Kaggle
Ctrl+K