Updated files

model_dir/config.json

@@ -0,0 +1,23 @@
+{
+  "_name_or_path": "shravvvv/SAG-ViT",
+  "architectures": [
+    "SAGViTClassifier"
+  ],
+  "d_model": 64,
+  "dim_feedforward": 64,
+  "gcn_hidden": 128,
+  "gcn_out": 64,
+  "hidden_mlp_features": 64,
+  "in_channels": 2560,
+  "model_type": "sagvit",
+  "nhead": 4,
+  "num_classes": 10,
+  "num_layers": 2,
+  "patch_size": [
+    4,
+    4
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.0",
+  "use_safetensors": true
+}

model_dir/pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3472578af5e4fd2f9644e94f8502895fc007abea1e6880364c0480b588c474a0
+size 32491922

push_model_to_hfhub.py

@@ -1,9 +1,10 @@
 from transformers import AutoConfig, AutoModel
-from modeling_sagvit import SAGViTClassifier
+from modeling_sagvit import SAGViTClassifier, SAGViTConfig
 
-# Initialize config and model
+# Load config and model
 config = AutoConfig.from_pretrained("shravvvv/SAG-ViT")
-model = AutoModel.from_pretrained("shravvvv/SAG-ViT", config=config)
+model = SAGViTClassifier(config)
 
-# Push model to the Hub
+# Save model locally before pushing
+model.save_pretrained("./model_dir", safe_serialization=False)  # Save in PyTorch format
 model.push_to_hub("shravvvv/SAG-ViT")

test_model_loading.py

@@ -1,6 +1,8 @@
-from transformers import AutoModelForImageClassification, AutoImageProcessor
+from transformers import AutoModel, AutoConfig
 
-model = AutoModelForImageClassification.from_pretrained("shravvvv/SAG-ViT", trust_remote_code=True)
-processor = AutoImageProcessor.from_pretrained("shravvvv/SAG-ViT", trust_remote_code=True)
+# Load Config and Model
+config = AutoConfig.from_pretrained("shravvvv/SAG-ViT")
+model = AutoModel.from_pretrained("shravvvv/SAG-ViT", config=config)
 
+# Check Model
 print(model)