Update README.md

README.md

@@ -21,9 +21,9 @@ pipeline_tag: text-generation
 ![Lamarck.webp](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.6/resolve/main/Lamarck.webp)
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-Lamarck 14B v0.6:  A generalist merge focused on multi-step reasoning, prose, and multi-language ability.  It is based on components that have punched above their weight in the 14 billion parameter class.  Here you can see a comparison between Lamarck and other top-performing merges and finetunes:
+> [!TIP] **Update:**  Lamarck has, for the moment, taken the [#1 average score](https://shorturl.at/STz7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) for text-generation assistant language models under 32 billion parameters.  Including 32 billion parameter models - more than twice Lamarck's size! - as of this writing, it's currently #10.  This validates the complex merge techniques which combine the strengths of other finetunes in the community into one model.
 
-**Update:**  Lamarck has, for the moment, taken the [#1 average score](https://shorturl.at/STz7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) for general 14B text-generation assistant language models - or even under 32 billion parameters.  Including 32 billion parameter models, as of this writing, it's currently #10.  This validates the complex merge techniques which combined the complementary strengths of other work in this community into one model.  A little layer analysis goes a long way.
+Lamarck 14B v0.6:  A generalist merge focused on multi-step reasoning, prose, and multi-language ability.  It is based on components that have punched above their weight in the 14 billion parameter class.  Here you can see a comparison between Lamarck and other top-performing merges and finetunes:
 
 ![Lamarck.webp](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.6/resolve/main/comparison.png)
 
@@ -137,4 +137,4 @@ slices:
 
 ```
 
-Lamarck's performance comes from an ancestry that goes back through careful merges to select finetuning work, upcycled and combined.  Kudoes to @arcee-ai, @CultriX, @sthenno-com, @Krystalan, @underwoods, @VAGOSolutions, and @rombodawg whose models had the most influence.  Of this model's immediate ancestors, [Vimarckoso v3](https://huggingface.co/sometimesanotion/Qwen2.5-14B-Vimarckoso-v3) has the model card which documents the other finetunes in its extended lineage.
+Lamarck's performance comes from an ancestry that goes back through careful merges to select finetuning work, upcycled and combined.  Kudoes to @arcee-ai, @CultriX, @sthenno-com, @Krystalan, @underwoods, @VAGOSolutions, and @rombodawg whose models had the most influence.  [Vimarckoso v3](https://huggingface.co/sometimesanotion/Qwen2.5-14B-Vimarckoso-v3) has the model card which documents its extended lineage.