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:
- 8639d28f47fb0dc1f1a292f77d568eada53aac67bcb0f693afd590e5a4781a21
- Size of remote file:
- 32.9 MB
- SHA256:
- dcbf7ceaa3c7a9cfa2dae00a824ef1b2e34264b99bb02f2d8f90c6c3c64b42ae
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