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:
- 2dedf656a3e7ee803630a561d84fd823bc2ab858b9adf3ac30adefe309052ed0
- Size of remote file:
- 5.76 kB
- SHA256:
- 41f1062bed267d07026bbe55dc5b8f17e4acc5cc1076fab42e1170bcb1ee4a54
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