# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("mitchelldehaven/whisper-medium-uk")
model = AutoModelForSpeechSeq2Seq.from_pretrained("mitchelldehaven/whisper-medium-uk")Quick Links
Whisper model finetuned using audio data from CommonVoice Ukrainian v10 train and dev set with additional data via semi-supervised data.
There is a differences in tokenization of source data (in our data normalization process, we replace punctucation with "" rather than Whisper's " "). This mismatch leads to a slight degradation on CommonVoice.
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Evaluation results
- WER on mozilla-foundation/common_voice_11_0test set self-reported14.550
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mitchelldehaven/whisper-medium-uk")