Update README.md

README.md

@@ -65,35 +65,3 @@ The following hyperparameters were used during training:
 
 
 
-import gradio as gr
-import torch
-from transformers import WhisperForConditionalGeneration, WhisperTokenizer
-
-torch.backends.cudnn.enabled = True
-
-# Load the speech-to-text model from Hugging Face
-model_name = "Ranjit/Whisper_v2.0"
-task = "transcribe"
-tokenizer = WhisperTokenizer.from_pretrained(model_name, task=task)
-model = WhisperForConditionalGeneration.from_pretrained(model_name).to("cuda")
-
-# Define a function to transcribe speech to text
-def transcribe_audio(audio):
-    input_values = tokenizer(audio, return_tensors="pt").input_values.to("cuda")
-    logits = model(input_values).logits
-    predicted_ids = torch.argmax(logits, dim=-1)
-    transcription = tokenizer.batch_decode(predicted_ids)[0]
-    return transcription
-
-# Create the Gradio interface
-gradio_interface = gr.Interface(
-    fn=transcribe_audio,
-    inputs="microphone",
-    outputs="text",
-    capture_session=True,  # Leverage GPU acceleration
-    title="Speech-to-Text",
-    description="Transcribe speech to text using a Wav2Vec2 model.",
-    theme="default",
-)
-
-gradio_interface.launch(share=True)