Instructions to use anzorq/w2v-bert-2.0-kbd-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anzorq/w2v-bert-2.0-kbd-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="anzorq/w2v-bert-2.0-kbd-v2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("anzorq/w2v-bert-2.0-kbd-v2") model = AutoModelForCTC.from_pretrained("anzorq/w2v-bert-2.0-kbd-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5740c4be379756557b942cef1220380c784f2ab54e7421bc535cf3c4d096c655
- Size of remote file:
- 4.92 kB
- SHA256:
- 383881821a886636d2b7f769ac89aac1b7a8ad973deb07a78b60900c49d93b82
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