I would like to know that which distribution does PyTorch follows now for the default initalisation of the weights and the biases? For example when I write something like -

The parameters are initialized in the reset_parameters method of the corresponding layer. For nn.Linear you can find the method here:

def reset_parameters(self) -> None:
# Setting a=sqrt(5) in kaiming_uniform is the same as initializing with
# uniform(-1/sqrt(in_features), 1/sqrt(in_features)). For details, see
# https://github.com/pytorch/pytorch/issues/57109
init.kaiming_uniform_(self.weight, a=math.sqrt(5))
if self.bias is not None:
fan_in, _ = init._calculate_fan_in_and_fan_out(self.weight)
bound = 1 / math.sqrt(fan_in) if fan_in > 0 else 0
init.uniform_(self.bias, -bound, bound)