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@@ -21,7 +21,7 @@ pipeline_tag: text-generation
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  ![Lamarck.webp](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.3/resolve/main/Lamarck.webp)
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  ---
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- ### Overview:
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  Lamarck-14B is a carefully designed merge which emphasizes [arcee-ai/Virtuoso-Small](https://huggingface.co/arcee-ai/Virtuoso-Small) in early and finishing layers, and midway features strong influence on reasoning and prose from [CultriX/SeQwence-14B-EvolMerge](http://huggingface.co/CultriX/SeQwence-14B-EvolMerge) especially, but a number of other models as well through its model_stock.
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@@ -46,7 +46,7 @@ The first two layers come entirely from Virtuoso. The choice to leave these lay
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  - @CultriX for the helpful examples of memory-efficient sliced merges and evolutionary merging. Their contribution of tinyevals on version 0.1 of Lamarck did much to validate the hypotheses of the DELLA->SLERP gradient process used here.
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  - The authors behind the capable models that appear in the model_stock. The boost to prose quality is already noticeable.
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- ### Models Merged:
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  **Top influences:** These ancestors are base models and present in the model_stocks, but are heavily re-emphasized in the DELLA and SLERP merges.
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  **Note on abliteration:** This author believes that adjacent services and not language models themselves are where guardrails are best placed. Effort to de-censor Lamarck will resume after the model has been further studied.
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- ### Configuration:
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- The following YAML configurations were used to produce this model:
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  ```yaml
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  name: lamarck-14b-reason-della # This contributes the knowledge and reasoning pool, later to be merged
 
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  ![Lamarck.webp](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.3/resolve/main/Lamarck.webp)
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  ---
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+ # merge
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  Lamarck-14B is a carefully designed merge which emphasizes [arcee-ai/Virtuoso-Small](https://huggingface.co/arcee-ai/Virtuoso-Small) in early and finishing layers, and midway features strong influence on reasoning and prose from [CultriX/SeQwence-14B-EvolMerge](http://huggingface.co/CultriX/SeQwence-14B-EvolMerge) especially, but a number of other models as well through its model_stock.
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  - @CultriX for the helpful examples of memory-efficient sliced merges and evolutionary merging. Their contribution of tinyevals on version 0.1 of Lamarck did much to validate the hypotheses of the DELLA->SLERP gradient process used here.
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  - The authors behind the capable models that appear in the model_stock. The boost to prose quality is already noticeable.
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+ ### Models Merged
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  **Top influences:** These ancestors are base models and present in the model_stocks, but are heavily re-emphasized in the DELLA and SLERP merges.
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  **Note on abliteration:** This author believes that adjacent services and not language models themselves are where guardrails are best placed. Effort to de-censor Lamarck will resume after the model has been further studied.
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+ ### Configuration
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+ The following YAML configuration was used to produce this model:
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  ```yaml
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  name: lamarck-14b-reason-della # This contributes the knowledge and reasoning pool, later to be merged