Update README.md

README.md

@@ -86,7 +86,7 @@ processor = Wav2Vec2Processor.from_pretrained("anas/wav2vec2-large-xlsr-arabic")
 model = Wav2Vec2ForCTC.from_pretrained("anas/wav2vec2-large-xlsr-arabic/")
 model.to("cuda")
 
-chars_to_ignore_regex = '[\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\؟\\\\\\\\\\\\\\\\.\\\\\\\\\\\\\\\\!\\\\\\\\\\\\\\\\-\\\\\\\\\\\\\\\\;\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\:\\\\\\\\\\\\\\\\'\\\\\\\\\\\\\\\\"\\\\\\\\\\\\\\\\☭\\\\\\\\\\\\\\\\«\\\\\\\\\\\\\\\\»\\\\\\\\\\\\\\\\؛\\\\\\\\\\\\\\\\—\\\\\\\\\\\\\\\\ـ\\\\\\\\\\\\\\\\_\\\\\\\\\\\\\\\\،\\\\\\\\\\\\\\\\“\\\\\\\\\\\\\\\\%\\\\\\\\\\\\\\\\‘\\\\\\\\\\\\\\\\”\\\\\\\\\\\\\\\\�]'
+chars_to_ignore_regex = '[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\؟\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\.\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\!\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\-\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\;\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\:\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\"\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\☭\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\«\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\»\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\؛\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\—\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ـ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\_\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\،\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\“\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\%\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\‘\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\”\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\�]'
 
 resampler = torchaudio.transforms.Resample(48_000, 16_000)
 
@@ -137,7 +137,7 @@ print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"],
 
 The Common Voice Corpus 4 `train`, `validation`, datasets were used for training
 
-The script used for training can be found [here](https://github.com/anashas/Fine-Tuning-of-XLSR-Wav2Vec2-on-Arabic/tree/master)
+The script used for training can be found [here](https://github.com/anashas/Fine-Tuning-of-XLSR-Wav2Vec2-on-Arabic)
 
 Twitter: [here](https://twitter.com/hasnii_anas)