Loading a pre-trained SwinV2 transformer and modifying the architecture

[SanaNazari]

I am trying to create a SwinV2 transformer model by loading pretrained weights and later modifying some Swin configurations, like the mlp ratio. Here is the sample class I am working on:

class Swin(nn.Module):
    def __init__(self,img_size, n_class, pretrained=False,mlp_ratio=4.,num_heads=[3, 6, 12, 24],depths=[2, 2, 6, 2],
window_size=7, attn_drop_rate=0., drop_path_rate =0.1,drop_rate=0.2,qkv_bias=True, embed_dim=96,):
        super().__init__()
        model_arch='timm/swin_tiny_patch4_window7_224.ms_in1k'
        self.config =  timm.create_model(model_arch, pretrained=pretrained).default_cfg
        self.config.image_size = img_size
        self.config.mlp_ratio = mlp_ratio   
        self.config.num_heads = num_heads
        self.config.depths = depths
        self.config.window_size = window_size
        self.config.embed_dim = embed_dim
        self.config.attention_probs_dropout_prob = attn_drop_rate
        self.config.drop_path_rate = drop_path_rate 
        self.config.drop_rate = drop_rate
        self.config.qkv_bias = qkv_bias
        self.config.num_classes = n_class
        print(self.config) 
        self.model =timm.create_model(model_arch,pretrained=pretrained, config=self.config)             
    def forward(self, x):
        x = self.model(x)
        return x

I get this error :

    self.config['mlp_ratio'] = mlp_ratio
  File "/home/sana/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1614, in __getattr__
    raise AttributeError("'{}' object has no attribute '{}'".format(
AttributeError: 'Swin' object has no attribute 'config'

Is there a way that I could implement this using timm library?