Instructions to use Na0s/Medical-Whisper-Large-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Na0s/Medical-Whisper-Large-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Na0s/Medical-Whisper-Large-v3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Na0s/Medical-Whisper-Large-v3") model = AutoModelForSpeechSeq2Seq.from_pretrained("Na0s/Medical-Whisper-Large-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Na0s/Medical-Whisper-Large-v3: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Na0s/Medical-Whisper-Large-v3/resolve/main/training_args.bin
- Command line
-
hf download hf://Na0s/Medical-Whisper-Large-v3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Na0s/Medical-Whisper-Large-v3/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 8fcfc2c5a6d8271f1357ad80215d77a3fb7b2625dff3fbfc431ade69b6e44c4f
- Size of remote file:
- 5.37 kB
- SHA256:
- 0f3fa9424d29b6dd226a58f45f5705f06c545e70f6a2cd8bf600f376a76c4081
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