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:
- b0f414482a47648ee38b601081dc46f6bde9e862888a1f21a4355f0c0cec963e
- Size of remote file:
- 4.91 GB
- SHA256:
- 151074e2c8338d3a2c61fe590b56a9bc96902e13c26c8ac019328218a7387f2e
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