sampling: add Top-nσ sampler

[VJHack]

Top-nσ: Not All Logits Are You Need

https://arxiv.org/pdf/2411.07641
The authors of this paper propose a new sampling method known as Top-nσ. The main feature of this sampler is that "unlike existing methods (e.g., top-p, min-p) that inadvertently include more noise tokens at higher temperatures, top-nσ maintains a stable sampling space regardless of temperature scaling". They discovered that logits natually separate into a gaussian-distributed noisy region and an informative region.

This PR implements the sampling method proposed in the paper. Here the algorithm implemented from the paper:

Since the manipulation is done directly on the logits pre-softmax, I added it as a stand-alone sampler instead of chaining it with the common samplers. The changes only add support for llama-cli.
sampler chain: logits -> logit-bias -> temp -> top-n-sigma -> dist

I'm aware that this algorithm is still in it's early phases so we could tag this as demo for now but I'll leave that choice up to the maintainers.

resolves #11057

Relavent Links:
https://huggingface.co/papers/2411.07641
https://arxiv.org/pdf/2411.07641
https://github.com/Tomorrowdawn/top_nsigma
#11057

[MaggotHATE]

Thank you for this implementation! Top-nσ is definitely special and needs a lot of testing.

I like the results so far, especially since high temperature is not a problem, as shown in the paper, and I'm going to test it more and see what its limitations are.