Instructions to use Semih/wav2vec2_Irish_Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Semih/wav2vec2_Irish_Large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Semih/wav2vec2_Irish_Large")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Semih/wav2vec2_Irish_Large") model = AutoModelForCTC.from_pretrained("Semih/wav2vec2_Irish_Large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfd720697d358d19c46b7fc897cae361bde94fc3d6f7fabc4f1d3b24357c3f7d
- Size of remote file:
- 2.29 kB
- SHA256:
- 2b7d572571609e537c0e66e68f42db627ce40f2bf69d6d178c3b1106b97f9bb7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.