More models and more tests to include?

[BradKML]

Sorry for a bit of a note insert, but there are lot of competitive fine tunes out there, for a more diverse set of benchmarks to test from, and I think OpenCompass might be useful in helping out evaluating overtrained models vs "accidental" general purpose models. LiveBench/LiveBench#95

Some questions I would like to ask:

• which benchmarks are more likely to correlate to one another when it comes to ranked performance?
• are finetuned models more likely to generalize between multiple tasks, or are there degredations?
• are abliterated (or ablated) models necessary worse than the foundation model it uses?
• are franken-merges like the ones in Sakana AI useful?