Upload 2 files

__init__.py

@@ -0,0 +1,11 @@
+
+# ---------------------------------------------------------------------------
+# Register the model with the Transformers library
+# ---------------------------------------------------------------------------
+from transformers import AutoConfig, AutoModel, AutoModelForSequenceClassification
+from .configuration_bert_ordinal import BertOrdinalConfig
+from .modeling_bert_ordinal import BertOrdinal
+
+AutoConfig.register("bert_ordinal", BertOrdinalConfig)
+AutoModel.register(BertOrdinalConfig, BertOrdinal)
+AutoModelForSequenceClassification.register(BertOrdinalConfig, BertOrdinal)

modeling_bert_ordinal.py

@@ -52,7 +52,7 @@ import torch.nn.functional as F
 from transformers import AutoModel, PreTrainedModel
 from transformers.modeling_outputs import ModelOutput
 
-from configuration_bert_ordinal import BertOrdinalConfig
+from .configuration_bert_ordinal import BertOrdinalConfig
 
 # ---------------------------------------------------------------------------
 # 1. Output dataclass
@@ -270,13 +270,3 @@ def ordinal_cross_entropy(
     reduction   : 'mean' | 'sum' | 'none'
     """
     return F.nll_loss(torch.log(class_probs), labels, reduction=reduction)
-
-
-# ---------------------------------------------------------------------------
-# Register the model with the Transformers library
-# ---------------------------------------------------------------------------
-from transformers import AutoConfig, AutoModel, AutoModelForSequenceClassification
-
-AutoConfig.register("bert_ordinal", BertOrdinalConfig)
-AutoModel.register(BertOrdinalConfig, BertOrdinal)
-AutoModelForSequenceClassification.register(BertOrdinalConfig, BertOrdinal)