Resolve "Flair Embeddings"

Closes #13

poldeepner2/utils/train_utils.py

@@ -182,3 +182,12 @@ def predict_model(model, eval_dataset, label_list, batch_size, device, report=Tr
           report = classification_report(y_true, y_pred, digits=4)
 
     return y_pred
+
+
+def countZeroWeights(model):
+    zeros = 0
+    for param in model.parameters():
+        if param is not None:
+               param = param.cpu()
+               zeros += param.numel() - param.nonzero().size(0)
+    return zeros
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