updated the link to the model

README.md

@@ -29,9 +29,9 @@ model-index:
 # Wav2Vec2-Large-XLSR-Turkish
 
 This is the model for Wav2Vec2-Large-XLSR-Turkish-Artificial-CV, a fine-tuned 
-[facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53)
-model on the Synthetic Turkish Voice dataset and
-[Turkish Common Voice dataset](https://huggingface.co/datasets/common_voice).
+[cahya/wav2vec2-large-xlsr-turkish-artificial](https://huggingface.co/cahya/wav2vec2-large-xlsr-turkish-artificial)
+model on [Turkish Common Voice dataset](https://huggingface.co/datasets/common_voice).
+
 When using this model, make sure that your speech input is sampled at 16kHz.
 
 ## Usage
@@ -44,8 +44,8 @@ from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
 
 test_dataset = load_dataset("common_voice", "tr", split="test[:2%]")
 
-processor = Wav2Vec2Processor.from_pretrained("cahya-wirawan/wav2vec2-large-xlsr-turkish-artificial-cv")
-model = Wav2Vec2ForCTC.from_pretrained("cahya-wirawan/wav2vec2-large-xlsr-turkish-artificial-cv")
+processor = Wav2Vec2Processor.from_pretrained("cahya/wav2vec2-large-xlsr-turkish-artificial-cv")
+model = Wav2Vec2ForCTC.from_pretrained("cahya/wav2vec2-large-xlsr-turkish-artificial-cv")
 
 
 # Preprocessing the datasets.
@@ -83,8 +83,8 @@ import re
 test_dataset = load_dataset("common_voice", "tr", split="test")
 wer = load_metric("wer")
 
-processor = Wav2Vec2Processor.from_pretrained("cahya-wirawan/wav2vec2-large-xlsr-turkish-artificial-cv")
-model = Wav2Vec2ForCTC.from_pretrained("cahya-wirawan/wav2vec2-large-xlsr-turkish-artificial-cv") 
+processor = Wav2Vec2Processor.from_pretrained("cahya/wav2vec2-large-xlsr-turkish-artificial-cv")
+model = Wav2Vec2ForCTC.from_pretrained("cahya/wav2vec2-large-xlsr-turkish-artificial-cv") 
 model.to("cuda")
 
 chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\‘\”\'\`…\’»«]'