Update README.md

README.md

@@ -43,8 +43,8 @@ from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
 
 test_dataset = load_dataset("common_voice", "tr", split="test[:2%]") 
 
-processor = Wav2Vec2Processor.from_pretrained("ceyda/wav2vec2-large-xlsr-turkish")
-model = Wav2Vec2ForCTC.from_pretrained("ceyda/wav2vec2-large-xlsr-turkish")
+processor = Wav2Vec2Processor.from_pretrained("ceyda/wav2vec2-large-xlsr-53-turkish")
+model = Wav2Vec2ForCTC.from_pretrained("ceyda/wav2vec2-large-xlsr-53-turkish")
 
 resampler = torchaudio.transforms.Resample(48_000, 16_000)
 
@@ -86,8 +86,8 @@ processor = Wav2Vec2Processor.from_pretrained("ceyda/wav2vec2-large-xlsr-turkish
 model = Wav2Vec2ForCTC.from_pretrained("ceyda/wav2vec2-large-xlsr-turkish")
 model.to("cuda")
 
-# chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“]'
-chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\%\‘\”\�\'\`]'
+# chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\“]'
+chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\“\\%\\‘\\”\\�\\'\\`]'
 resampler = torchaudio.transforms.Resample(48_000, 16_000)
 
 # Preprocessing the datasets.