Update app.py

app.py

@@ -13,7 +13,7 @@ import csv
 import datetime
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-MODEL_NAME="nvidia/parakeet-tdt-0.6b-v2"
+MODEL_NAME="Quantumhash/Quantum_STT_V2.0"
 
 model = ASRModel.from_pretrained(model_name=MODEL_NAME)
 model.eval()
@@ -313,24 +313,17 @@ def play_segment(evt: gr.SelectData, raw_ts_list, current_audio_path):
 
 article = (
     "<p style='font-size: 1.1em;'>"
-    "This demo showcases <code><a href='https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2'>parakeet-tdt-0.6b-v2</a></code>, a 600-million-parameter model designed for high-quality English speech recognition."
+    "This demo showcases <code><a href='https://huggingface.co/Quantumhash/Quantum_STT_V2.0</a></code>, a 600-million-parameter model designed for high-quality English speech recognition."
     "</p>"
     "<p><strong style='color: red; font-size: 1.2em;'>Key Features:</strong></p>"
     "<ul style='font-size: 1.1em;'>"
     "    <li>Automatic punctuation and capitalization</li>"
     "    <li>Accurate word-level timestamps (click on a segment in the table below to play it!)</li>"
-    "    <li>Efficiently transcribes long audio segments (<strong>updated to support upto 3 hours</strong>) <small>(For even longer audios, see <a href='https://github.com/NVIDIA/NeMo/blob/main/examples/asr/asr_chunked_inference/rnnt/speech_to_text_buffered_infer_rnnt.py' target='_blank'>this script</a>)</small></li>"
+    "    <li>Efficiently transcribes long audio segments (<strong>updated to support upto 3 hours</strong>)</li>"
     "    <li>Robust performance on spoken numbers, and song lyrics transcription </li>"
     "</ul>"
     "<p style='font-size: 1.1em;'>"
     "This model is <strong>available for commercial and non-commercial use</strong>."
-    "</p>"
-    "<p style='text-align: center;'>"
-    "<a href='https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2' target='_blank'>🎙️ Learn more about the Model</a> | "
-    "<a href='https://arxiv.org/abs/2305.05084' target='_blank'>📄 Fast Conformer paper</a> | "
-    "<a href='https://arxiv.org/abs/2304.06795' target='_blank'>📚 TDT paper</a> | "
-    "<a href='https://github.com/NVIDIA/NeMo' target='_blank'>🧑‍💻 NeMo Repository</a>"
-    "</p>"
 )
 
 examples = [