Instructions to use Umong/w2v-bert-2.0-ben10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Umong/w2v-bert-2.0-ben10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Umong/w2v-bert-2.0-ben10")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Umong/w2v-bert-2.0-ben10") model = AutoModelForCTC.from_pretrained("Umong/w2v-bert-2.0-ben10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34724ca220a4688c0951ec0da3753c6a7a529f29251f1f4c248615c694d158a6
- Size of remote file:
- 4.92 kB
- SHA256:
- a44cbdcfd9934dc6d17b9f56b5a82ea7da4a80cb0daebe0d5645d79cf8688680
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