Instructions to use sengtha/whisper-tiny-khmer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sengtha/whisper-tiny-khmer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sengtha/whisper-tiny-khmer")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sengtha/whisper-tiny-khmer") model = AutoModelForSpeechSeq2Seq.from_pretrained("sengtha/whisper-tiny-khmer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39f301376232b901bd607e445a63a48e3427ef59bbc587f4cf8276ae5fdac3d6
- Size of remote file:
- 5.39 kB
- SHA256:
- 721724870a8f062f4513a7c145c144ed620c63fcf4fd0df05ee16bf5b67591f6
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