It doesn't make sense for c_crossattn and c_concat to be lists.

comfy/model_base.py

@@ -50,10 +50,10 @@ class BaseModel(torch.nn.Module):
 
     def apply_model(self, x, t, c_concat=None, c_crossattn=None, c_adm=None, control=None, transformer_options={}):
         if c_concat is not None:
-            xc = torch.cat([x] + c_concat, dim=1)
+            xc = torch.cat([x] + [c_concat], dim=1)
         else:
             xc = x
-        context = torch.cat(c_crossattn, 1)
+        context = c_crossattn
         dtype = self.get_dtype()
         xc = xc.to(dtype)
         t = t.to(dtype)

comfy/samplers.py

@@ -165,9 +165,9 @@ def sampling_function(model_function, x, timestep, uncond, cond, cond_scale, con
                 c_crossattn_out.append(c)
 
             if len(c_crossattn_out) > 0:
-                out['c_crossattn'] = [torch.cat(c_crossattn_out)]
+                out['c_crossattn'] = torch.cat(c_crossattn_out)
             if len(c_concat) > 0:
-                out['c_concat'] = [torch.cat(c_concat)]
+                out['c_concat'] = torch.cat(c_concat)
             if len(c_adm) > 0:
                 out['c_adm'] = torch.cat(c_adm)
             return out