diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index 7d81a69ec..635b2bd61 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -1522,16 +1522,16 @@ class DbrxModel(Model):
             n_ff = self.hparams["ffn_config"]["ffn_hidden_size"]
             n_embd = self.hparams["d_model"]
 
-            # Specific behavior for experts tensors: suffix .weight, reshape to 3D
+            # Specific behavior for experts tensors: suffix .weight, reshape to 3D and transpose
             # orginal implementation expects (n_expert, n_ff, n_embd)
-            exp_tensor_names = {"ffn.experts.mlp.v1",  # LLM_TENSOR_FFN_GATE_EXPS ne {n_embd, n_ff,   n_expert}
-                                "ffn.experts.mlp.w2",  # LLM_TENSOR_FFN_DOWN_EXPS ne {n_ff,   n_embd, n_expert}
-                                "ffn.experts.mlp.w1"}  # LLM_TENSOR_FFN_UP_EXPS   ne {n_embd, n_ff,   n_expert }
+            exp_tensor_names = {"ffn.experts.mlp.v1": (0, 1, 2),  # LLM_TENSOR_FFN_GATE_EXPS(n_embd, n_ff,   n_expert)
+                                "ffn.experts.mlp.w2": (0, 2, 1),  # LLM_TENSOR_FFN_DOWN_EXPS(n_ff,   n_embd, n_expert)
+                                "ffn.experts.mlp.w1": (0, 1, 2)}  # LLM_TENSOR_FFN_UP_EXPS  (n_embd, n_ff,   n_expert)
             experts = False
-            for exp_tensor_name in exp_tensor_names:
+            for exp_tensor_name in exp_tensor_names.keys():
                 if name.find(exp_tensor_name) != -1 and name.find(".weight") == -1:
                     experts = True
-                    data_torch = data_torch.view(n_expert, n_ff, n_embd)
+                    data_torch = data_torch.view(n_expert, n_ff, n_embd).permute(*exp_tensor_names[exp_tensor_name])
                     break
 
             old_dtype = data_torch.dtype