diff --git a/src/resnet.jl b/src/resnet.jl
index bdea58e47..65a865b34 100644
--- a/src/resnet.jl
+++ b/src/resnet.jl
@@ -39,8 +39,7 @@ function Bottleneck(filters::Int, downsample::Bool = false, res_top::Bool = fals
   end
 end
 
-function resnet50()
-  local layers = [3, 4, 6, 3]
+function resnet(layers = [3,4,6,3])
   local layer_arr = []
 
   push!(layer_arr, Conv((7,7), 3=>64, pad = (3,3), stride = (2,2)))
@@ -63,24 +62,24 @@ function resnet50()
   Chain(layer_arr...)
 end
 
-function resnet_layers()
-  weight = Metalhead.weights("resnet.bson")
-  weights = Dict{Any ,Any}()
-  for ele in keys(weight)
-    weights[string(ele)] = convert(Array{Float64, N} where N, weight[ele])
-  end
-  ls = resnet50()
-  ls[1].weight .= weights["gpu_0/conv1_w_0"][end:-1:1,:,:,:][:,end:-1:1,:,:]
-  count = 2
-  for j in [3:5, 6:9, 10:15, 16:18]
-    for p in j
-      ls[p].conv_layers[1].weight .= weights["gpu_0/res$(count)_$(p-j[1])_branch2a_w_0"][end:-1:1,:,:,:][:,end:-1:1,:,:]
-      ls[p].conv_layers[2].weight .= weights["gpu_0/res$(count)_$(p-j[1])_branch2b_w_0"][end:-1:1,:,:,:][:,end:-1:1,:,:]
-      ls[p].conv_layers[3].weight .= weights["gpu_0/res$(count)_$(p-j[1])_branch2c_w_0"][end:-1:1,:,:,:][:,end:-1:1,:,:]
-    end
-    count += 1
-  end
-  ls[21].W .= transpose(weights["gpu_0/pred_w_0"]); ls[21].b .= weights["gpu_0/pred_b_0"]
+function resnet_layers(layers = [3,4,6,3])
+  # weight = Metalhead.weights("resnet.bson")
+  # weights = Dict{Any ,Any}()
+  # for ele in keys(weight)
+  #   weights[string(ele)] = convert(Array{Float64, N} where N, weight[ele])
+  # end
+  ls = resnet(layers)
+  # ls[1].weight .= weights["gpu_0/conv1_w_0"][end:-1:1,:,:,:][:,end:-1:1,:,:]
+  # count = 2
+  # for j in [3:5, 6:9, 10:15, 16:18]
+  #   for p in j
+  #     ls[p].conv_layers[1].weight .= weights["gpu_0/res$(count)_$(p-j[1])_branch2a_w_0"][end:-1:1,:,:,:][:,end:-1:1,:,:]
+  #     ls[p].conv_layers[2].weight .= weights["gpu_0/res$(count)_$(p-j[1])_branch2b_w_0"][end:-1:1,:,:,:][:,end:-1:1,:,:]
+  #     ls[p].conv_layers[3].weight .= weights["gpu_0/res$(count)_$(p-j[1])_branch2c_w_0"][end:-1:1,:,:,:][:,end:-1:1,:,:]
+  #   end
+  #   count += 1
+  # end
+  # ls[21].W .= transpose(weights["gpu_0/pred_w_0"]); ls[21].b .= weights["gpu_0/pred_b_0"]
   return ls
 end
 
@@ -89,6 +88,9 @@ struct ResNet <: ClassificationModel{ImageNet.ImageNet1k}
 end
 
 ResNet() = ResNet(resnet_layers())
+ResNet50() = ResNet()
+ResNet101() = ResNet(resnet_layers([3,4,23,3]))
+ResNet152() = ResNet(resnet_layers([3,8,36,3]))
 
 Base.show(io::IO, ::ResNet) = print(io, "ResNet()")