inference_code_snippet_added

README.md

@@ -51,8 +51,8 @@ In order to infer a single audio file using this model, the following code snipp
 >>> device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
 >>> transcribe = pipeline(task="automatic-speech-recognition", model="vasista22/whisper-kannada-base", chunk_length_s=30, device=device)
-
 >>> transcribe.model.config.forced_decoder_ids = transcribe.tokenizer.get_decoder_prompt_ids(language="kn", task="transcribe")
+
 >>> print('Transcription: ', transcribe(audio)["text"])
 ```
 
@@ -83,6 +83,6 @@ The following hyperparameters were used during training:
 - mixed_precision_training: True
 
 ## Acknowledgement
-This work was done at [Speech Lab, IITM](https://asr.iitm.ac.in/).
+This work was done at [Speech Lab, IIT Madras](https://asr.iitm.ac.in/).
 
 The compute resources for this work were funded by "Bhashini: National Language translation Mission" project of the Ministry of Electronics and Information Technology (MeitY), Government of India.