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example.py

@@ -0,0 +1,15 @@
+import numpy as np
+from transformers import AutoModel
+
+# Load sm_subgroup_classifier
+sm_classifier = AutoModel.from_pretrained(
+    "erikhenriksson/sm-subgroup-classifier", trust_remote_code=True
+)
+
+# create a random 1024 dimensional embedding
+
+embedding = np.random.rand(1024).astype(np.float32)
+
+# Use - model automatically discovers what's available
+result = sm_classifier("en", "OP-ob", embedding)
+print(f"Prediction: {result['predictions']['predicted_class']}")

modeling_sm_subgroup_classifier.py

@@ -120,6 +120,13 @@ class SmSubgroupClassifier(PreTrainedModel):
 
     @classmethod
     def from_pretrained(cls, pretrained_model_name_or_path, **kwargs):
-        model = super().from_pretrained(pretrained_model_name_or_path, **kwargs)
+        # Load config
+        config = SmSubgroupClassifierConfig.from_pretrained(
+            pretrained_model_name_or_path, **kwargs
+        )
+
+        # Create model instance (skip the pytorch weight loading)
+        model = cls(config)
         model.model_dir = pretrained_model_name_or_path
+
         return model