Instructions to use Hanhpt23/whisper-base-chinesemed-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hanhpt23/whisper-base-chinesemed-full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Hanhpt23/whisper-base-chinesemed-full")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Hanhpt23/whisper-base-chinesemed-full") model = AutoModelForSpeechSeq2Seq.from_pretrained("Hanhpt23/whisper-base-chinesemed-full") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20f5e395911b744218b8e97bf6fc62f1b2b74d0f5ae15f1e76af087614f22161
- Size of remote file:
- 290 MB
- SHA256:
- c6ff52b098c4a21ef64bcbeff95f73636c5eb9cba31c624e1323e7091ac82df8
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