sometimesanotion
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README.md
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pipeline_tag: text-generation
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---
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![Lamarck.webp](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.6/resolve/main/Lamarck.webp)
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Lamarck 14B v0.6:
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## Merge Details
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[sometimesanotion/Qwen2.5-14B-Vimarckoso-v3](https://huggingface.co/sometimesanotion/Qwen2.5-14B-Vimarckoso-v3)
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[sometimesanotion/Lamarck-14B-v0.3](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.3)
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[sometimesanotion/Qwenvergence-14B-v3-Prose](https://huggingface.co/sometimesanotion/Qwenvergence-14B-v3-Prose)
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[Krystalan/DRT-o1-14B](https://huggingface.co/Krystalan/DRT-o1-14B)
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[underwoods/medius-erebus-magnum-14b](https://huggingface.co/underwoods/medius-erebus-magnum-14b)
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[sometimesanotion/Abliterate-Qwenvergence](https://huggingface.co/sometimesanotion/Abliterate-Qwenvergence) - A custom version of [huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2](https://huggingface.co/huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2)
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### Configuration
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The following YAML configurations were used to initialize and finalize this model:
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This model was made in two branches: a della_linear merge, and a sequence of model_stock and then breadcrumbs SLERP-merged below.
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```yaml
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- accuracy
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pipeline_tag: text-generation
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---
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![Lamarck.webp](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.6-rc4/resolve/main/Lamarck.webp)
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---
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Lamarck 14B v0.6: A generalist merge focused on multi-step reasoning, prose, multi-language ability, and code. It is based on components that have punched above their weight in the 14 billion parameter class.
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Previous releases were based on a SLERP merge of model_stock->della branches focused on reasoning and prose. The prose branch got surprisingly good at reasoning, and the reasoning branch being the base for IFEVAL became an all-around generalist. Some of you have already downloaded the reasoning branch, released as [sometimesanotion/Qwen2.5-14B-Vimarckoso-v3](https://huggingface.co/sometimesanotion/Qwen2.5-14B-Vimarckoso-v3).
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Lamarck 0.6 aims to build upon Vimarckoso v3's all-around strength with strong buffs to prose and translation quality, and strong reasoning for its class. Updates to come as leaderboards become available to evaluate it in-depth.
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## Merge Details
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[sometimesanotion/Qwen2.5-14B-Vimarckoso-v3](https://huggingface.co/sometimesanotion/Qwen2.5-14B-Vimarckoso-v3)
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[sometimesanotion/Lamarck-14B-v0.3](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.3)
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[sometimesanotion/Qwenvergence-14B-v3-Prose](https://huggingface.co/sometimesanotion/Qwenvergence-14B-v3-Prose) - a model_stock merge of multiple prose-oriented models which posts surprisingly high MATH, GPQA, and MUSR scores.
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[Krystalan/DRT-o1-14B](https://huggingface.co/Krystalan/DRT-o1-14B) - A particularly interesting model which applies extra reasoning to language translation. Check out their fascinating research paper at [arxiv.org/abs/2412.17498](https://arxiv.org/abs/2412.17498).
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[underwoods/medius-erebus-magnum-14b](https://huggingface.co/underwoods/medius-erebus-magnum-14b)
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[sometimesanotion/Abliterate-Qwenvergence](https://huggingface.co/sometimesanotion/Abliterate-Qwenvergence) - A custom version of [huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2](https://huggingface.co/huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2)
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### Configuration
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This model was made in two branches: a della_linear merge, and a sequence of model_stock and then breadcrumbs SLERP-merged below.
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```yaml
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