Instructions to use danielbubiola/daniel_asr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielbubiola/daniel_asr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="danielbubiola/daniel_asr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("danielbubiola/daniel_asr") model = AutoModelForCTC.from_pretrained("danielbubiola/daniel_asr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c78cdf1b25eddb68229b03321304db736db53ca41f56e300e211740c16a39f4
- Size of remote file:
- 2.8 kB
- SHA256:
- cd5a951151ec6e5ef61c7c45d59be22989b5010429fc518821b851da7c996cf0
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