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| import gradio as gr | |
| import nemo.collections.asr as nemo_asr | |
| from nemo.collections.asr.models import ASRModel | |
| import os | |
| from huggingface_hub import hf_hub_download | |
| # Download model from private repo | |
| model_path = hf_hub_download( | |
| repo_id="KnowlAI/parakeet-rnnt-0.6b-08122025-11.55", | |
| filename="parakeet-knowl-hindi.nemo", | |
| token=os.environ.get("HF_TOKEN") | |
| ) | |
| asr_model = ASRModel.restore_from(model_path) | |
| def transcribe_audio(audio): | |
| """Transcribe audio file""" | |
| if audio is None: | |
| return "Please upload or record an audio file." | |
| try: | |
| # Transcribe | |
| transcription = asr_model.transcribe([audio]) | |
| return transcription[0] | |
| except Exception as e: | |
| return f"Error: {str(e)}" | |
| def greet(name): | |
| return "Hello " + name + "!!" | |
| demo = gr.Interface( | |
| fn=transcribe_audio, | |
| inputs=gr.Audio(type="filepath", label="Upload or Record Audio"), | |
| outputs=gr.Textbox(label="Transcription (Hindi)", lines=5), | |
| title="Parakeet Hindi ASR Demo", | |
| description="Upload or record Hindi speech to get the transcription. This model was trained for 100,000 steps on Hindi speech data." | |
| ) | |
| #demo = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| demo.launch() | |