Mixtral 8x7B network support for thunder.jit path

Nobody has claimed this yet.

## 🚀 Feature

Mixtral 8x7B is a mixture-of-experts LLM that splits the parameters in 8 distinct groups an I would like to do both training and inference with Thunder.

### Work items
- [x] Run `thunder.examine`
- [ ] #124
- [ ] #195
- [x] #187
- [ ] #303
- [ ] Create Mixtral benchmark

### Additional context
Even though `examine` does not signal any problem with the ops, some testing revealed that Mixtral uses `torch.where(condition)` signature of the `torch.where` function which is not supported at the moment. Moreover, the second issue I was able to identify stems from the indexing done in Mixtral forward function. At the moment, the `_advanced_indexing` clang operation does not take into account `None` as a valid index together with other tensors.

Start with the Mixtral forward path and the reported `torch.where(condition)` call, then inspect the `_advanced_indexing` clang operation and run `thunder.examine`. Done means Mixtral training and inference work through the `thunder.jit` path, with the listed indexing and where cases covered and a Mixtral benchmark created.

Written by the indexing model from the issue text.