Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Khmer
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use ksoky/whisper-small-km with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ksoky/whisper-small-km with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ksoky/whisper-small-km")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ksoky/whisper-small-km") model = AutoModelForMultimodalLM.from_pretrained("ksoky/whisper-small-km") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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## Model description
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The model was fine-tuned on both encoder-decoder of transformer-based.
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## Intended uses & limitations
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The training data is limited, thus the performance is also limited to only reading speech and a limited domain (tourism).
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## Training and evaluation data
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The training and evaluation data was split in a 9:1 ratio from Google Text-to-speech corpus.
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## Training procedure
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