I was looking around for ages trying to figure this out and couldn’t find any examples so here is what used which was stupidly simple in the end 
def image_loader(image_name):
    image = Image.open(image_name)
    image = loader(image).float()
    image = Variable(image, requires_grad=True)
    image = image.unsqueeze(0)  #this is for VGG, may not be needed for ResNet
    return image.cuda()  #assumes that you're using GPU

image = image_loader('/var/www/html/' + filename)

net = torch.load('resnet50_trained3.pth')
print(net)

net.eval()
output = net(image)
print(output) #print output from crossentropy score

sm = torch.nn.Softmax()
probabilities = sm(output) 
print(probabilities) #Converted to probabilities