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:
- ae2aff9bbb1ab5113524e03facbea56b819bb81d13bb37cd33c6324e6d6f7f49
- Size of remote file:
- 4.91 GB
- SHA256:
- 0bf3c0896fc412abffc4a6d4f829c8cdd4510d93606af5eb9ce43c576f81ef80
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