google/fleurs
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How to use seanghay/whisper-small-khmer-v2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="seanghay/whisper-small-khmer-v2") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("seanghay/whisper-small-khmer-v2")
model = AutoModelForSpeechSeq2Seq.from_pretrained("seanghay/whisper-small-khmer-v2")This model is a fine-tuned version of openai/whisper-small on the openslr, google/fleurs and km-speech-corpus dataset.
It achieves the following results on the evaluation set:
This model is fine-tuned with Google FLEURS, OpenSLR (SLR42) and km-speech-corpus dataset.
from transformers import pipeline
pipe = pipeline(
task="automatic-speech-recognition",
model="seanghay/whisper-small-khmer-v2",
)
result = pipe("audio.wav",
generate_kwargs={
"language":"<|km|>",
"task":"transcribe"},
batch_size=16
)
print(result["text"])