Update README.md

README.md

@@ -11,7 +11,7 @@ tags:
 - speech-recognition
 ---
 
-# NavaiSTT-2v Medium - Uzbek Speech-to-Text Model
+# rubaiSTT-2v Medium - Uzbek Speech-to-Text Model
 
 Classic Whisper medium model fine-tuned for Uzbek language. The dataset included of diverse audio: publicly available podcasts, Tashkent dialect podcasts, news, google fleurs, USC and Common Voice 17. Data quality was mixed with 50% human transcribed and 50% pseudo-transcribed using Gemini 2.5 Pro.
 
@@ -20,9 +20,9 @@ Difference between v1 is that v2 is fully open-sourced. Due to some conflicts wi
 Special attention was given to Tashkent dialect audio materials, resulting in strong performance on this dialect. Future versions will include other regional dialects to improve overall coverage.
 
 # Whitepaper
-For more details on the methodology and research behind this model, visit: https://uz-speech.web.app/navaistt02m
+For more details on the methodology and research behind this model, visit: https://uz-speech.web.app/rubaistt02m
 
-Training and filtering code: https://github.com/Islomov49/navaistt_v2-open-sourced
+Training and filtering code: https://github.com/Islomov49/rubaistt_v2-open-sourced
 
 Support my works and open-source movement: https://tirikchilik.uz/islomovs
 
@@ -56,8 +56,8 @@ import torchaudio
 from transformers import WhisperProcessor, WhisperForConditionalGeneration
 
 # Load model and processor
-processor = WhisperProcessor.from_pretrained("islomov/navaistt_v2_medium")
-model = WhisperForConditionalGeneration.from_pretrained("islomov/navaistt_v2_medium")
+processor = WhisperProcessor.from_pretrained("islomov/rubaistt_v2_medium")
+model = WhisperForConditionalGeneration.from_pretrained("islomov/rubaistt_v2_medium")
 
 def transcribe_audio(audio_path):