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:
- e81e3f3cce26b1916045d981b88c1a50bed3f31bb7a4b8cf990a6360481cf876
- Size of remote file:
- 4.91 GB
- SHA256:
- 5b79b67d01a8d514d966d6698d028c24c8812371dd8c97741cab3f28c44a27d9
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