Update inference_wav2vec.yaml

inference_wav2vec.yaml

@@ -10,7 +10,7 @@
 # #################################
 
 # pretrain folders:
-pretrained_path: ./
+pretrained_path: TalTechNLP/voxlingua107-xls-r-300m-wav2vec
 
 # Model parameters
 sample_rate: 16000
@@ -22,8 +22,8 @@ compute_features: !new:speechbrain.lobes.features.Fbank
 
 ######################## Wav2Vec ########################
 # URL for the wav2vec2 model.
-wav2vec2_hub: TalTechNLP/voxlingua107-xls-r-300m-wav2vec
-freeze_wav2vec: True # False
+wav2vec2_hub: facebook/wav2vec2-xls-r-300m
+freeze_wav2vec: True 
 save_folder: ./save
 
 wav2vec2: !new:speechbrain.lobes.models.huggingface_wav2vec.HuggingFaceWav2Vec2
@@ -48,11 +48,11 @@ attentive: !new:speechbrain.lobes.models.ECAPA_TDNN.AttentiveStatisticsPooling
     attention_channels: 64 
 
 modules:
-    wav2vec2: !ref <wav2vec2> # Added
+    wav2vec2: !ref <wav2vec2>
     compute_features: !ref <compute_features>
     classifier: !ref <classifier>
-    attentive: !ref <attentive> # Added
-    softmax: !ref <softmax> # Added
+    attentive: !ref <attentive> 
+    softmax: !ref <softmax>
 
 model: !new:torch.nn.ModuleList
    - [!ref <attentive>, !ref <classifier>]
@@ -66,7 +66,7 @@ pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
     paths:
         wav2vec2: !ref <pretrained_path>/wav2vec2.ckpt
         classifier: !ref <pretrained_path>/classifier.ckpt
-        label_encoder: <pretrained_path>/label_encoder.txt
+        label_encoder: !ref <pretrained_path>/label_encoder.txt
         model: !ref <pretrained_path>/model.ckpt
 
 ##################