Update README.md

README.md

@@ -22,7 +22,7 @@ widget:
 - example_title: Librispeech sample 2
   src: https://cdn-media.huggingface.co/speech_samples/sample2.flac
 model-index:
-- name: parakeet-tdt-0.6b-v2
+- name: Quantum_STT_V2.0
   results:
   - task:
       name: Automatic Speech Recognition
@@ -155,16 +155,15 @@ img {
 
 ## <span style="color:#466f00;">Description:</span>
 
-`parakeet-tdt-0.6b-v2` is a 600-million-parameter automatic speech recognition (ASR) model designed for high-quality English transcription, featuring support for punctuation, capitalization, and accurate timestamp prediction. Try Demo here: https://huggingface.co/spaces/nvidia/parakeet-tdt-0.6b-v2 
+`Quantum_STT_V2.0` is a 600-million-parameter automatic speech recognition (ASR) model designed for high-quality English transcription, featuring support for punctuation, capitalization, and accurate timestamp prediction. Try Demo here: https://huggingface.co/spaces/Quantamhash/Quantum_STT_V2.0 
 
-This XL variant of the FastConformer [1] architecture integrates the TDT [2] decoder and is trained with full attention, enabling efficient transcription of audio segments up to 24 minutes in a single pass. The model achieves an RTFx of 3380 on the HF-Open-ASR leaderboard with a batch size of 128. Note: *RTFx Performance may vary depending on dataset audio duration and batch size.*  
+This XL variant of the FastConformer [1] architecture integrates the TDT [2] decoder and is trained with full attention, enabling efficient transcription of audio segments up to 24 minutes in a single pass.
 
 **Key Features**
 - Accurate word-level timestamp predictions  
 - Automatic punctuation and capitalization  
 - Robust performance on spoken numbers, and song lyrics transcription 
 
-For more information, refer to the [Model Architecture](#model-architecture) section and the [NeMo documentation](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/asr/models.html#fast-conformer).
 
 This model is ready for commercial/non-commercial use.
 
@@ -185,7 +184,7 @@ This model serves developers, researchers, academics, and industries building ap
 
 ### <span style="color:#466f00;">Release Date:</span>
 
-05/01/2025
+14/05/2025
 
 ### <span style="color:#466f00;">Model Architecture:</span>