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:
- 6b469e836e60ac35e5b42e7f20398731d6851bdcbe8d2191be717d8cd4688b65
- Size of remote file:
- 4.91 GB
- SHA256:
- 4d4cc7a6c58fabcb86b66424f100472b743d74b5ac624b38a68e77a1285f0d19
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