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:
- 4bd1c9152cb6969f4fedb2062172c5dd566c29405dc2507c293d138e56971eb0
- Size of remote file:
- 4.91 GB
- SHA256:
- 0c65dcf59f04d943e39cb4492c400192d4b6ec599e07b64d6f77cb97e0df3ee7
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