Model unchanged.

This is commit description!

config.json

@@ -1,10 +1,10 @@
 {
   "architectures": [
-    "ResnetModelForImageClassification"
+    "MyResnetModelForImageClassification"
   ],
   "auto_map": {
-    "AutoConfig": "configuration_resnet.ResnetConfig",
-    "AutoModelForImageClassification": "modeling_resnet.ResnetModelForImageClassification"
+    "AutoConfig": "configuration_resnet.MyResnetConfig",
+    "AutoModelForImageClassification": "modeling_resnet.MyResnetModelForImageClassification"
   },
   "avg_down": true,
   "base_width": 64,
@@ -17,7 +17,7 @@
     6,
     3
   ],
-  "model_type": "resnet",
+  "model_type": "MyResnet",
   "num_classes": 1000,
   "stem_type": "deep",
   "stem_width": 32,

configuration_resnet.py

@@ -2,8 +2,8 @@ from transformers import PretrainedConfig
 from typing import List
 
 
-class ResnetConfig(PretrainedConfig):
-    model_type = "resnet"
+class MyResnetConfig(PretrainedConfig):
+    model_type = "MyResnet"
 
     def __init__(
             self,

modeling_resnet.py

@@ -1,13 +1,13 @@
 from transformers import PreTrainedModel
 from timm.models.resnet import BasicBlock, Bottleneck, ResNet
-from .configuration_resnet import ResnetConfig
+from .configuration_resnet import MyResnetConfig
 import torch
 
 BLOCK_MAPPING = {"basic": BasicBlock, "bottleneck": Bottleneck}
 
 
-class ResnetModel(PreTrainedModel):
-    config_class = ResnetConfig
+class MyResnetModel(PreTrainedModel):
+    config_class = MyResnetConfig
 
     def __init__(self, config):
         super().__init__(config)
@@ -28,8 +28,8 @@ class ResnetModel(PreTrainedModel):
         return self.model.forward_features(tensor)
 
 
-class ResnetModelForImageClassification(PreTrainedModel):
-    config_class = ResnetConfig
+class MyResnetModelForImageClassification(PreTrainedModel):
+    config_class = MyResnetConfig
 
     def __init__(self, config):
         super().__init__(config)