Instructions to use Hanhpt23/whisper-tiny-Encode-chinesemed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hanhpt23/whisper-tiny-Encode-chinesemed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Hanhpt23/whisper-tiny-Encode-chinesemed")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Hanhpt23/whisper-tiny-Encode-chinesemed") model = AutoModelForSpeechSeq2Seq.from_pretrained("Hanhpt23/whisper-tiny-Encode-chinesemed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4aa2cf04fd80155d7c4dc8711adeeca8572c338972c14f0859b64d5d5346a24e
- Size of remote file:
- 5.3 kB
- SHA256:
- f5afb5b0ab88dc7a853b33e85e4825f4833e24b4ec391aac221b1fb01a6ba1a8
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