whisper-tiny-khmer-mlx-fp16
This model was converted to MLX format from openai-whisper-tiny
, then fine-tined to Khmer language using two datasets:
It achieves the following word error rate (wer
) on 2 popular datasets:
- 80.2% on
test
split of google/fleurskm-kh
- 63.2% on
train
split of openslr/openslrSLR42
NOTE MLX format is usable for M-chip series of Apple.
Use with mlx
pip install mlx-whisper
Write a python script, example.py
, as the following
import mlx_whisper
result = mlx_whisper.transcribe(
SPEECH_FILE_NAME,
path_or_hf_repo="Kimang18/whisper-tiny-khmer-mlx-fp16",
fp16=True
)
print(result['text'])
Then execute this script example.py
to see the result.
You can also use command line in terminal
mlx_whisper --model Kimang18/whisper-tiny-khmer-mlx-fp16 --task transcribe SPEECH_FILE_NAME --fp16 True
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HF Inference deployability: The HF Inference API does not support automatic-speech-recognition models for mlx
library.
Dataset used to train Kimang18/whisper-tiny-khmer-mlx-fp16
Evaluation results
- test on test split of "km_kh" in google/fleursself-reported80.2%
- test on train split of "SLR42" in openslr/openslrself-reported63.2%