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whisper-base-khmer-mlx-fp32 – AI Model by Kimang18 | AlphaNeural AI

You can deploy this model and start earning money today!

Kimang18/
whisper-base-khmer-mlx-fp32

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automatic-speech-recognition

seanghay/km-speech-corpus

seanghay/khmer_mwpt_speech

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whisper-base-khmer-mlx-fp32

This model was converted to MLX format from openai-whisper-base, then fine-tined to Khmer language using three datasets:

seanghay/khmer_mpwt_speech
seanghay/km-speech-corpus
train split of openslr/openslr SLR42

It achieves the following word error rate (wer) on 2 popular datasets:

69.7% on test split of google/fleurs km-kh

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

python

import mlx_whisper

result = mlx_whisper.transcribe(
    SPEECH_FILE_NAME,
    path_or_hf_repo="mlx-community/whisper-base-khmer-mlx-fp32",
    fp16=False
)
print(result['text'])

Then execute this script example.py to see the result.

You can also use command line in terminal

mlx_whisper --model mlx-community/whisper-base-khmer-mlx-fp32 --task transcribe SPEECH_FILE_NAME --fp16 False