Instructions to use todeschini/medical-whisper-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use todeschini/medical-whisper-pt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="todeschini/medical-whisper-pt")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("todeschini/medical-whisper-pt") model = AutoModelForSpeechSeq2Seq.from_pretrained("todeschini/medical-whisper-pt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b75fdc2ee4ef5d5c15677018ede23ad19666668807d4f05d62d3f17378c73f7c
- Size of remote file:
- 11.8 kB
- SHA256:
- 92527cb70a2d6fe32447fc8220639884bce64cfac5dde989dda9a84da4a75c21
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