Instructions to use codingninja/w2v-pa-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codingninja/w2v-pa-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="codingninja/w2v-pa-v2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("codingninja/w2v-pa-v2") model = AutoModelForCTC.from_pretrained("codingninja/w2v-pa-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f50dc21c6191e01997d806b27cfa4ad22ce732261506ee28db087c4fe6eef6eb
- Size of remote file:
- 4.91 GB
- SHA256:
- 34ae6125657a97a33b1d08310a8bc83ee660f79c8c83b497b8b7a0fdf839cb92
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