Update README

Author: LukasHedegaard

README.md

@@ -247,14 +247,16 @@ results = benchmark(model, sample, num_runs=100)
   ```
 </details>
 
-## Limitations
-Usage assumptions:
-- The model has as a `__call__` method that takes the sample, i.e. `model(sample)`.
-- The Model works for any batch size (first dimension).
+... Your turn
+
+## Advanced use
+Trying to benchmark a custom class, which is not a `torch.nn.Module`?
+- You can pass custom functions to `benchmark` as seen in [this example](tests/test_custom_class.py).
 
-Feature limitations:
+## Limitations
 - Allocated memory measurements are only available on CUDA devices.
 - Energy consumption can only be measured on NVIDIA Jetson platforms at the moment.
+- FLOPs and parameters count is not support for custom classes.
 
 
 ## Citation