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base_model:
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- unsloth/Mistral-Small-Instruct-2409
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- unsloth/Mistral-Small-Instruct-2409
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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#
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### Models Merged
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The following models were included in the merge:
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* [unsloth/Mistral-Small-Instruct-2409](https://huggingface.co/unsloth/Mistral-Small-Instruct-2409)
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* [unsloth/Mistral-Small-Instruct-2409](https://huggingface.co/unsloth/Mistral-Small-Instruct-2409) + [The-Company/Acolyte-LORA-Proper-e2](https://huggingface.co/The-Company/Acolyte-LORA-Proper-e2)
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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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models:
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- model: unsloth/Mistral-Small-Instruct-2409+The-Company/Acolyte-LORA-Proper-e2
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- model: unsloth/Mistral-Small-Instruct-2409
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merge_method: slerp
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base_model: unsloth/Mistral-Small-Instruct-2409
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parameters:
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t: 0.5
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dtype: bfloat16
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```
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base_model:
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- unsloth/Mistral-Small-Instruct-2409
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- unsloth/Mistral-Small-Instruct-2409
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- rAIfle/Acolyte-LORA
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# Acolyte-22B
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LoRA of a bunch of random datasets on top of Mistral-Small-Instruct-2409, then SLERPed onto base at 0.5. Decent enough for its size.
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Check the LoRA for dataset info.
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Use `Mistral V2 & V3` template.
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