AlphaFold2.ipynb on Colab running out of memory

I am trying to run a ~800 residues protein (WP_086691035.1 colicin uptake protein [Nostoc sp. T09]) through the AlphaFold2 ipython notebook on colab.

However, I am running out of memory. Shorter sequences work fine and I remember running a sequence of similar length earlier. Do you know if there is a way of getting a successful run at some point in time, for example when the load is lower e.g. during the weekend? I know there a payed plan but I would only use it for running the notebook and it is not clear how much resources each plan actually has. It just says that the payed plan has “more” CPU and RAM but that is not that helpful.

running model_1
---------------------------------------------------------------------------
UnfilteredStackTrace                      Traceback (most recent call last)
<ipython-input-13-af48741e914e> in <module>()
     50                          model_params=model_params, use_model=use_model,
---> 51                          do_relax=use_amber)

13 frames
UnfilteredStackTrace: RuntimeError: RESOURCE_EXHAUSTED: Out of memory while trying to allocate 10409975032 bytes.

The stack trace below excludes JAX-internal frames.
The preceding is the original exception that occurred, unmodified.

--------------------

The above exception was the direct cause of the following exception:

RuntimeError                              Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/jax/interpreters/xla.py in _execute_compiled(compiled, avals, handlers, kept_var_idx, *args)
    958           for i, x in enumerate(args)
    959           if x is not token and i in kept_var_idx))
--> 960   out_bufs = compiled.execute(input_bufs)
    961   check_special(xla_call_p.name, out_bufs)
    962   return [handler(*bs) for handler, bs in zip(handlers, _partition_outputs(avals, out_bufs))]

RuntimeError: RESOURCE_EXHAUSTED: Out of memory while trying to allocate 10409975032 bytes.