Instructions to use phongdtd/wavLM-VLSP-vi-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phongdtd/wavLM-VLSP-vi-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="phongdtd/wavLM-VLSP-vi-large")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("phongdtd/wavLM-VLSP-vi-large") model = AutoModelForCTC.from_pretrained("phongdtd/wavLM-VLSP-vi-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f9eed939b6b8bdf98b4b599357467ceef199d668131895f0fef43f4e9be66fa
- Size of remote file:
- 3.06 kB
- SHA256:
- 2b308a2062f632a5af5dde27b7ca3b2920fb6208ad8df315e8cd5993015a9e36
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