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README.md

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 > [!TIP] With no 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] The first DPO finetune of Lamarck has appeared!  Check out [jpacifico/Chocolatine-2-14B-Instruct-v2.0b2](http://huggingface.co/jpacifico/Chocolatine-2-14B-Instruct-v2.0b2), 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!
+> [!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!
 
 Lamarck 14B v0.7:  A generalist merge with emphasis on multi-step reasoning, prose, and multi-language ability.  The 14B parameter model class has a lot of strong performers, and Lamarck strives to be well-rounded and solid: ![14b.png](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.7/resolve/main/14b.png)