Update README.md

README.md

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 ![Lamarck.webp](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.7/resolve/main/LamarckShades.webp)
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-> [!TIP] With no benchmark regressions, mostly gains over the previous release, this version of Lamarck has [broken the 41.0 average](https://shorturl.at/jUqEk) maximum for 14B parameter models.  As of this writing, Lamarck v0.7 ranks #8 among models under 70B parameters on the Open LLM Leaderboard.  Given the quality models in the 32B range, I think Lamarck deserves his shades.  A little layer analysis of a model in the 14B range goes a long, long way.
+> [!TIP] With no benchmark regressions, mostly gains over the previous release, this version of Lamarck has [broken the 41.0 average](https://shorturl.at/jUqEk) maximum for 14B parameter models.  A little layer analysis of a model in the 14B range goes a long, long way.
 
 > [!TIP] The first DPO finetune of Lamarck has appeared!  Check out [jpacifico/Chocolatine-2-14B-Instruct-v2.0b3](http://huggingface.co/jpacifico/Chocolatine-2-14B-Instruct-v2.0b3), whose notes say, "The Chocolatine model series is a quick demonstration that a base model can be easily fine-tuned to achieve compelling performance."  Lamarck's painstaking merge process was intended to make finetuning to a desired polish as easy and energy-efficient as possible.  Thank you, @jpacifico!