Add VeRA support

**Is your feature request related to a problem? Please describe:**
LoRA is designed to reduce the memory requirements to finetune LLMs and already exists in Fairseq2 to some capacity. [VeRA](https://arxiv.org/abs/2308.03303) reduces the memory overhead of [vanilla LoRA](https://arxiv.org/abs/2310.11454) even further by training a single vector that is treated as a diagonal matrix that is multiplied by two other matrices initialized using a normal distribution.

**Describe the solution you would like:**
There should be a separate class to wrap models with VeRA like there is currently with LoRA and a premade recipe would also be nice to have.

**Describe the alternatives you have considered:**
None

**Additional Context:**
None

Start by locating the existing LoRA model wrapper and premade recipe in Fairseq2, then read the linked VeRA paper to understand the requested parameterization. Done means Fairseq2 has a separate VeRA wrapper and a premade recipe, with coverage comparable to the current LoRA support.

Written by the indexing model from the issue text.