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:
- 10f3a3f4826ebd5264870639e58ef4dbc1e3cfe2ae03d01a0d183311f3789c06
- Size of remote file:
- 40.5 MB
- SHA256:
- 0e3319f974acab05d7f0afb97917ee2947ba448b7db2c812b5ae643b0015d66a
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