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:
- f9ef0b9f5f370ee6f343d4124d2e5e01bcb3066570ade63c2f76834c0f114c7e
- Size of remote file:
- 4.91 GB
- SHA256:
- d59bce46ac9e4ea12853ab969a9507ffec7beff43979ca9439a2f5e52e6e6914
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