MuASR-3B-v0.1

from transformers import VoxtralForConditionalGeneration, AutoProcessor
import torch

device = "cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu"
repo_id = "mrfakename/MuASR-3B"

processor = AutoProcessor.from_pretrained(repo_id)
model = VoxtralForConditionalGeneration.from_pretrained(repo_id, dtype=torch.bfloat16, device_map=device)

inputs = processor.apply_transcription_request(language="en", audio="assets/song_full.mp3", model_id=repo_id)
inputs = inputs.to(device, dtype=torch.bfloat16)

outputs = model.generate(
    **inputs,
    max_new_tokens=500,
    do_sample=True
)
decoded_outputs = processor.batch_decode(outputs[:, inputs.input_ids.shape[1]:], skip_special_tokens=True)

print("\nGenerated responses:")
print("=" * 80)
for decoded_output in decoded_outputs:
    print(decoded_output)
    print("=" * 80)