Update model.py

model.py

@@ -9,26 +9,7 @@ import torch
 import torch.nn as nn
 import transformers
 
-
-class ContextualModelConfig(transformers.configuration_utils.PretrainedConfig):
-    """We create a dummy configuration class that will just set properties
-    based on whatever kwargs we pass in.
-
-    When this class is initialized (see experiments.py) we pass in the
-    union of all data, model, and training args, all of which should
-    get saved to the config json.
-    """
-
-    def __init__(self, **kwargs):
-        for key, value in kwargs.items():
-            try:
-                json.dumps(value)
-                setattr(self, key, value)
-            except TypeError:
-                # value was not JSON-serializable, skip
-                continue
-        super().__init__()
-
+from misc import ContextualModelConfig
 
 def load_embedder_and_tokenizer(name: str) -> Tuple[
         transformers.PreTrainedModel,