Update pipeline.py

pipeline.py

@@ -52,8 +52,8 @@ class PreTrainedPipeline():
         print('Init')
         self.sampling_rate = 16000
         
-        self.processor = Wav2Vec2Processor.from_pretrained('.')
-        self.model = Wav2Vec2ForCTC.from_pretrained('.')
+        self.processor = Wav2Vec2Processor.from_pretrained(path)
+        self.model = Wav2Vec2ForCTC.from_pretrained(path)
         self.group_ids = [sorted(self.processor.tokenizer.convert_tokens_to_ids(group)) for group in groups]
         self.group_ids = [dict([(x[0]+1,x[1]) for x in list(enumerate(g))]) for g in self.group_ids] #This is the inversion of the one used in training as here we need to map prediction back to original tokens