Update README.md

README.md

@@ -28,10 +28,10 @@ model-index:
       value: 99.8077099166743
 ---
 
-# Fine-tuned Whisper Medium for Hindi Language
+# iVaani 
 
 # Model Description
-This model is a fine-tuned version of OpenAI's Whisper medium model, specifically optimized for the Hindi language. The fine-tuning process has led to an improvement in accuracy by 2.5% compared to the original Whisper model.
+This is iVaani model, specifically optimized for the Hindi language. The fine-tuning process has led to an improvement in accuracy by 2.5% compared to the original Whisper model.
 
 # Performance
 After fine-tuning, the model shows a 2.5% increase in transcription accuracy for Hindi language audio compared to the base Whisper medium model.
@@ -42,8 +42,8 @@ You can use this model directly with a simple API call in Hugging Face. Here is
 ```python
 from transformers import AutoModelForCTC, Wav2Vec2Processor
 
-model = AutoModelForCTC.from_pretrained("rukaiyah-indika-ai/whisper-medium-hindi-fine-tuned")
-processor = Wav2Vec2Processor.from_pretrained("rukaiyah-indika-ai/whisper-medium-hindi-fine-tuned")
+model = AutoModelForCTC.from_pretrained("rukaiyah-indika-ai/iVaani")
+processor = Wav2Vec2Processor.from_pretrained("rukaiyah-indika-ai/iVaani")
 
 # Replace 'path_to_audio_file' with the path to your Hindi audio file
 input_audio = processor(path_to_audio_file, return_tensors="pt", padding=True)
@@ -78,7 +78,7 @@ If you use this model in your research, please cite it as follows:
 ```bibtex
 @misc{whisper-medium-hindi-fine-tuned,
   author = {Indika AI},
-  title = {Fine-tuned Whisper Medium for Hindi Language},
+  title = {iVaani},
   year = {2024},
   publisher = {Hugging Face},
   journal = {Hugging Face Model Hub}