Instructions to use Hanhpt23/whisper-base-Encode-chinesemed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hanhpt23/whisper-base-Encode-chinesemed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Hanhpt23/whisper-base-Encode-chinesemed")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Hanhpt23/whisper-base-Encode-chinesemed") model = AutoModelForSpeechSeq2Seq.from_pretrained("Hanhpt23/whisper-base-Encode-chinesemed") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfaeff3f93e063c5413d4e50229ec8a27f6cd7375f482c82d451a5f1b61fb660
- Size of remote file:
- 5.3 kB
- SHA256:
- f43b4d0d134bfe31f8f1760bc6046425621b47e40d5b45ba170a39ee4b05902b
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