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:
- 1a2bd4408574be56397a3ccc049e1f2c1d714d5841d715e9db3286e079ae3476
- Size of remote file:
- 60.8 kB
- SHA256:
- 27c3d420df69bf7c4fb8989274ab42298dec885bbf07efd62a9a02d48c673d98
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