from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import torch

processor = Wav2Vec2Processor.from_pretrained("vitthalbhandari/mms-1b-all-aft-3h-hch")
model = Wav2Vec2ForCTC.from_pretrained("vitthalbhandari/mms-1b-all-aft-3h-hch")

# Load adapter
model.load_adapter("hch")

# Transcribe audio
inputs = processor(audio_array, sampling_rate=16000, return_tensors="pt")
with torch.no_grad():
    logits = model(**inputs).logits
predicted_ids = torch.argmax(logits, dim=-1)
transcription = processor.batch_decode(predicted_ids)