Instructions to use ctaguchi/w2v-bert-2.0-gui with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ctaguchi/w2v-bert-2.0-gui with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ctaguchi/w2v-bert-2.0-gui")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ctaguchi/w2v-bert-2.0-gui") model = AutoModelForCTC.from_pretrained("ctaguchi/w2v-bert-2.0-gui", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2dee3c06c7411e9b665c02718cb902059e5b2aa3e7ef3276cd061ccaace65afd
- Size of remote file:
- 5.27 kB
- SHA256:
- 0b3ca8b651d2646b4293ebdee75f84188a8d426539f2447f3c4c4319f3eedd72
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