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:
- 4f55700e5ff6fafcf5bb315c1c943ebd4e29e51ea8e0e40b127cefd2dd65bc29
- Size of remote file:
- 378 MB
- SHA256:
- 9f45f89434263633fa30d59a9d43699e43a5dbe2b3a09daa88c07746c48681ed
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