Upload Resnet50FER

config.json

@@ -1,7 +1,12 @@
 {
+  "architectures": [
+    "Resnet50FER"
+  ],
   "auto_map": {
-    "AutoConfig": "config.Resnet50Config"
+    "AutoConfig": "config.Resnet50Config",
+    "AutoModelForImageClassification": "model.Resnet50FER"
   },
   "num_classes": 6,
+  "torch_dtype": "float32",
   "transformers_version": "4.37.2"
 }

model.py

@@ -0,0 +1,22 @@
+import torch
+import torch.nn as nn
+import torchvision.models as models
+from .config import Resnet50Config
+from transformers import PreTrainedModel
+
+class Resnet50FER(PreTrainedModel):
+    config = Resnet50Config
+    def __init__(self, config):
+        super().__init__(config)
+        # Load the ResNet50 model without the final fully connected layer
+        self.resnet = models.resnet50(pretrained=False)
+        
+        num_ftrs = self.resnet.fc.in_features
+        # Replace the fully connected layer with a new one for your specific classification task
+        self.resnet.fc = nn.Linear(num_ftrs, config.num_classes)
+
+    def forward(self, x):
+        # Forward pass through the ResNet50 model
+        x = self.resnet(x)
+        x = self.resnet.fc(x)
+        return x

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0eee7468c7e125b5499bb7d42c79b8261da5cd6aa07e9dd571e761f6edba8bbc
+size 94324992