Upload folder using huggingface_hub

example.py

@@ -6,9 +6,6 @@ sm_classifier = AutoModel.from_pretrained(
     "erikhenriksson/sm-subgroup-classifier", trust_remote_code=True
 )
 
-available = sm_classifier._get_available_models()
-print(f"Available models on HF Hub: {available}")
-
 # create a random 1024 dimensional embedding
 
 embedding = np.random.rand(1024).astype(np.float32)

modeling_sm_subgroup_classifier.py

@@ -110,6 +110,15 @@ class SmSubgroupClassifier(PreTrainedModel):
 
         # Create model instance (skip the pytorch weight loading)
         model = cls(config)
-        model.model_dir = pretrained_model_name_or_path
+
+        # For HF Hub, we need to resolve to the actual cached directory
+        try:
+            from huggingface_hub import snapshot_download
+
+            # Download/get the cached directory path
+            model.model_dir = snapshot_download(pretrained_model_name_or_path)
+        except ImportError:
+            # Fallback if huggingface_hub not available
+            model.model_dir = pretrained_model_name_or_path
 
         return model