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README.md
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---
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###
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source: TareksLab/M-TOKENIZER-SCE
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chat_template: llama3
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dtype: bfloat16
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```
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---
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base_model_relation: quantized
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base_model:
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- TareksTesting/Legion-V1A-LLaMa-70B
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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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# merge
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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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### Merge Method
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This model was merged using the [DARE TIES](https://arxiv.org/abs/2311.03099) merge method using [TareksLab/M-BASE-SCE](https://huggingface.co/TareksLab/M-BASE-SCE) 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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* [TareksLab/M-MERGE1](https://huggingface.co/TareksLab/M-MERGE1)
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* [TareksLab/M-MERGE3](https://huggingface.co/TareksLab/M-MERGE3)
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* [TareksLab/M-MERGE2](https://huggingface.co/TareksLab/M-MERGE2)
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* [TareksLab/M-MERGE4](https://huggingface.co/TareksLab/M-MERGE4)
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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: TareksLab/M-MERGE4
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parameters:
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weight:
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- filter: self_attn
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value: [0.3, 0.1, 0.2]
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- filter: mlp
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value: [0.4, 0.2, 0.1]
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- value: 0.2
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density: 0.7
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lambda: 1.05
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- model: TareksLab/M-MERGE3
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parameters:
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weight:
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- filter: self_attn
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value: [0.2, 0.1, 0.3]
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- filter: mlp
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value: [0.3, 0.1, 0.2]
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- value: 0.2
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density: 0.65
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lambda: 1.05
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- model: TareksLab/M-MERGE2
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parameters:
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weight:
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- filter: self_attn
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value: [0.1, 0.3, 0.1]
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- filter: mlp
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value: [0.2, 0.3, 0.1]
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- value: 0.2
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density: 0.6
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lambda: 1.05
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- model: TareksLab/M-MERGE1
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parameters:
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weight:
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- filter: self_attn
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value: [0.2, 0.2, 0.1]
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- filter: mlp
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value: [0.1, 0.2, 0.2]
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- value: 0.2
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density: 0.6
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lambda: 1
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- model: TareksLab/M-BASE-SCE
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parameters:
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weight:
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- filter: self_attn
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value: [0.1, 0.3, 0.3]
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- filter: mlp
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value: [0.1, 0.2, 0.4]
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- value: 0.2
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density: 0.55
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lambda: 1
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base_model: TareksLab/M-BASE-SCE
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merge_method: dare_ties
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parameters:
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normalize: false
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pad_to_multiple_of: 4
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tokenizer:
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source: TareksLab/M-TOKENIZER-SCE
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chat_template: llama3
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dtype: bfloat16
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```
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