Instructions to use duclee9x/wav2vec2-voa-example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use duclee9x/wav2vec2-voa-example with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="duclee9x/wav2vec2-voa-example")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("duclee9x/wav2vec2-voa-example") model = AutoModelForCTC.from_pretrained("duclee9x/wav2vec2-voa-example", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
add tokenizer
4a3119d -
add tokenizer
d9e4c81 -
add tokenizer
b5fe8a0 -
add tokenizer
50c29c7 -
add tokenizer
c5cdcac -
add tokenizer
0ed5332 -
update model card README.md
0e8c7b4 -
End of training
3127d99
-
add tokenizer
a225e5c -
initial commit
dbbef3e