Upload config

config.json

@@ -1,19 +1,18 @@
-{
-  "architectures": [
-    "BERTMultiAttentionModel"
-  ],
-    "auto_map": {
-    "AutoConfig": "config.BERTMultiAttentionConfig",
-    "AutoModel": "model.BERTMultiAttentionModel"
-  },
-  "dropout": 0.1,
-  "hidden_size": 768,
-  "model_type": "bert_multi_attention",
-  "num_heads": 8,
-  "rnn_bidirectional": true,
-  "rnn_hidden_size": 128,
-  "rnn_num_layers": 2,
-  "torch_dtype": "float32",
-  "transformer": "bert-base-uncased",
-  "transformers_version": "4.38.2"
-}
+{
+  "architectures": [
+    "BERTMultiAttentionModel"
+  ],
+  "auto_map": {
+    "AutoConfig": "config.BERTMultiAttentionConfig"
+  },
+  "dropout": 0.1,
+  "hidden_size": 768,
+  "model_type": "bert_multi_attention",
+  "num_heads": 8,
+  "rnn_bidirectional": true,
+  "rnn_hidden_size": 128,
+  "rnn_num_layers": 2,
+  "torch_dtype": "float32",
+  "transformer": "bert-base-uncased",
+  "transformers_version": "4.37.2"
+}

config.py

@@ -1,28 +1,28 @@
-from transformers import PretrainedConfig, AutoConfig
-
-class BERTMultiAttentionConfig(PretrainedConfig):
-    model_type = "bert_multi_attention"
-   # keys_to_ignore_at_inference = ["dropout"]
-
-    def __init__(
-        self,
-        transformer="bert-base-uncased",
-        hidden_size=768,
-        num_heads=8,
-        dropout=0.1,
-        rnn_hidden_size=128,
-        rnn_num_layers=2,
-        rnn_bidirectional=True,
-        **kwargs
-    ):
-        super().__init__(**kwargs)
-        self.transformer = transformer
-        self.hidden_size = hidden_size
-        self.num_heads = num_heads
-        self.dropout = dropout
-        self.rnn_hidden_size = rnn_hidden_size
-        self.rnn_num_layers = rnn_num_layers
-        self.rnn_bidirectional = rnn_bidirectional
-
-
-AutoConfig.register("bert_multi_attention", BERTMultiAttentionConfig)
+from transformers import PretrainedConfig, AutoConfig
+
+class BERTMultiAttentionConfig(PretrainedConfig):
+    model_type = "bert_multi_attention"
+    keys_to_ignore_at_inference = ["dropout"]
+
+    def __init__(
+        self,
+        transformer="bert-base-uncased",
+        hidden_size=768,
+        num_heads=8,
+        dropout=0.1,
+        rnn_hidden_size=128,
+        rnn_num_layers=2,
+        rnn_bidirectional=True,
+        **kwargs
+    ):
+        super().__init__(**kwargs)
+        self.transformer = transformer
+        self.hidden_size = hidden_size
+        self.num_heads = num_heads
+        self.dropout = dropout
+        self.rnn_hidden_size = rnn_hidden_size
+        self.rnn_num_layers = rnn_num_layers
+        self.rnn_bidirectional = rnn_bidirectional
+
+
+AutoConfig.register("bert_multi_attention", BERTMultiAttentionConfig)