How to use UBC-NLP/Simba-X with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="UBC-NLP/Simba-X")
# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("UBC-NLP/Simba-X") model = AutoModelForCTC.from_pretrained("UBC-NLP/Simba-X")
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{ "do_normalize": true, "feature_extractor_type": "Wav2Vec2FeatureExtractor", "feature_size": 1, "padding_side": "right", "padding_value": 0, "return_attention_mask": true, "sampling_rate": 16000 }
