If I understand correctly you can use
for name, param in model.named_parameters():
   # Just an example
   if 'weight' in name:
         param.data == torch.zeros_like(param)
   elif 'bias' in name:
         param.data == torch.zeros_like(param) 

If you do this the param will reflect the changes back without adding a step to the gradient tape.