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README.md
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base_model: []
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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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# LuminumMistral-123B
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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---
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base_model: []
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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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# LuminumMistral-123B
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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I present Luminum.
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This is a merge using Mistral Large as a base, and including Lumimaid-v0.2-123B and Magnum-v2-123B.
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I felt like Magnum was rambling too much, and Lumimaid lost slightly too much brain power, so I used Mistral Large base, but it was lacking some moist.
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On a whim, I decided to merge both Lumimaid and Magnum on top of Mistral large, and while I wasn't expecting much, I've been very surprised with the results.
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I've tested this model quite extensively at and above 32k with great success. It should in theory allow for the full 128k context, albeit I've only went to 40-50k max.
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It's become my new daily driver.
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I'll update the model card and add artwork tomorrow, am tired.
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### Merge Method
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This model was merged using the della_linear merge method using mistralaiMistral-Large-Instruct-2407 as a base.
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### Models Merged
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The following models were included in the merge:
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* NeverSleepLumimaid-v0.2-123B
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* anthracite-orgmagnum-v2-123b
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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: anthracite-orgmagnum-v2-123b
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parameters:
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weight: 0.19
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density: 0.5
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- model: NeverSleepLumimaid-v0.2-123B
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parameters:
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weight: 0.34
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density: 0.8
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merge_method: della_linear
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base_model: mistralaiMistral-Large-Instruct-2407
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parameters:
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epsilon: 0.05
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lambda: 1
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int8_mask: true
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dtype: bfloat16
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```
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