Automatic Speech Recognition
Transformers
TensorBoard
ONNX
Safetensors
Khmer
whisper
khmer
speech-to-text
asr
ggml
on-device
iany
Eval Results (legacy)
Instructions to use sengtha/whisper-base-khmer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sengtha/whisper-base-khmer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sengtha/whisper-base-khmer")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sengtha/whisper-base-khmer") model = AutoModelForSpeechSeq2Seq.from_pretrained("sengtha/whisper-base-khmer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8139d5fe80e368435bc807368b404542c20a161e3110508253ebc8d12cb52139
- Size of remote file:
- 5.39 kB
- SHA256:
- 560557bdf3b9ce0fe30d738b19682aa8d1c3b8d8a6439fd6886717e3f89b70f6
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