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  ![Lamarck.webp](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.7/resolve/main/LamarckShades.webp)
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- > [!TIP] This version of the model has [broken the 41.0 average](https://shorturl.at/jUqEk) maximum for 14B parameter models, and as of this writing, ranks #8 among models under 70B parameters on the Open LLM Leaderboard. Given the respectable performance in the 32B range, I think Lamarck deserves his shades. A little layer analysis in the 14B range goes a long, long way.
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  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)
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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 regressions, only gains over the previous release, this version of Lamarck has [broken the 41.0 average](https://shorturl.at/jUqEk) maximum for 14B parameter models, and as of this writing, ranks #8 among models under 70B parameters on the Open LLM Leaderboard. Given the respectable performance in the 32B range, I think Lamarck deserves his shades. A little layer analysis in the 14B range goes a long, long way.
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  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)
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