| from transformers import AutoModel, AutoTokenizer | |
| import torch | |
| REPO_ID = "bharatgenai/Shrutam-2" | |
| model = AutoModel.from_pretrained(REPO_ID, trust_remote_code=True) | |
| tokenizer = AutoTokenizer.from_pretrained(REPO_ID) | |
| model.to("cuda" if torch.cuda.is_available() else "cpu") | |
| model.eval() | |
| prompt = "Transcribe speech to Hindi text." | |
| # Single file | |
| print(model.transcribe("audio.wav", prompts=prompt, tokenizer=tokenizer)) | |
| # Batch inference — one prompt per file | |
| wavs = ["clip_hi.wav", "clip_mr.wav", "clip_ta.wav"] | |
| prompts = [ | |
| "Transcribe speech to Hindi text.", | |
| "Transcribe speech to Marathi text.", | |
| "Transcribe speech to Tamil text.", | |
| ] | |
| print(model.transcribe(wavs, prompts=prompts, batch_size=2, tokenizer=tokenizer)) | |