Instructions to use ctaguchi/w2v-bert-2.0-gui-ufe 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-ufe 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-ufe")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ctaguchi/w2v-bert-2.0-gui-ufe") model = AutoModelForCTC.from_pretrained("ctaguchi/w2v-bert-2.0-gui-ufe", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f47083ee3b0a471545baf93aab91ed326f572b78b917ed02e529435ae4f9784
- Size of remote file:
- 5.27 kB
- SHA256:
- d483753e50b0bcb05dca8d51620bb0975c7a3c19d5eb95f764e5b36e833e448c
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