You could use the functional API to apply the parameters to an input.
The weight and bias arrays seem to be used in linear layers, so something like this should work:
x = torch.randn(10, 10) # your input
weight = nn.Parameter(torch.from_numpy(your_weight_array))
bias = nn.Parameter(torch.from_numpy(your_bias_array))

out = F.linear(x, weight, bias)

Additionally, in case you want to train these parameters, pass them to an optimizer and apply the standard training loop.