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--- |
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base_model: |
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- TareksLab/MO-MODEL3-V0.2-LLaMa-70B |
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- TareksLab/MO-MODEL5-V0.3-LLaMa-70B |
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- TareksLab/MO-MODEL2-V0.2-LLaMa-70B |
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- TareksLab/MO-MODEL1-V1-LLaMa-70B |
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- TareksLab/MO-MODEL6-V0.1-LLaMa-70B |
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- TareksLab/MO-MODEL4-V0.1-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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license: llama3.3 |
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--- |
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 |
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Formerly known as MO-MODEL-Fused-V0.6-LLaMa-70B, This model is part of my ongoing experiments with merging specialized curated models. For this one, I started experimenting with gradients, to give myself more finetuned control of how the models influence the final merge. |
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Recommended sampler settings: |
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``` |
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Temp 1.0 |
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Min P 0.02 |
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``` |
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Because of the nature of this sort of 'Hyper Multi Model Merge', my recommendation is not to run this on anything lower than a Q5 quant. |
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If you enjoy my work, please consider supporting me, It helps me make more models like this! |
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[Support on KO-FI <3](https://ko-fi.com/tarek07) |
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# MERGE2 |
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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/MO-MODEL6-V0.1-LLaMa-70B](https://huggingface.co/TareksLab/MO-MODEL6-V0.1-LLaMa-70B) 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/MO-MODEL3-V0.2-LLaMa-70B](https://huggingface.co/TareksLab/MO-MODEL3-V0.2-LLaMa-70B) |
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* [TareksLab/MO-MODEL5-V0.3-LLaMa-70B](https://huggingface.co/TareksLab/MO-MODEL5-V0.3-LLaMa-70B) |
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* [TareksLab/MO-MODEL2-V0.2-LLaMa-70B](https://huggingface.co/TareksLab/MO-MODEL2-V0.2-LLaMa-70B) |
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* [TareksLab/MO-MODEL1-V1-LLaMa-70B](https://huggingface.co/TareksLab/MO-MODEL1-V1-LLaMa-70B) |
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* [TareksLab/MO-MODEL4-V0.1-LLaMa-70B](https://huggingface.co/TareksLab/MO-MODEL4-V0.1-LLaMa-70B) |
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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/MO-MODEL6-V0.1-LLaMa-70B |
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parameters: |
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weight: [0.1, 0.1, 0.1, 0.2, 0.5] |
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density: 0.5 |
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- model: TareksLab/MO-MODEL4-V0.1-LLaMa-70B |
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parameters: |
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weight: [0.1, 0.1, 0.2, 0.4, 0.2] |
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density: 0.5 |
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- model: TareksLab/MO-MODEL5-V0.3-LLaMa-70B |
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parameters: |
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weight: [0.1, 0.2, 0.4, 0.2, 0.1] |
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density: 0.5 |
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- model: TareksLab/MO-MODEL3-V0.2-LLaMa-70B |
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parameters: |
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weight: [0.2, 0.4, 0.2, 0.1, 0.1] |
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density: 0.5 |
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- model: TareksLab/MO-MODEL2-V0.2-LLaMa-70B |
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parameters: |
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weight: [0.5, 0.2, 0.1, 0.1, 0.1] |
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density: 0.5 |
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- model: TareksLab/MO-MODEL1-V1-LLaMa-70B |
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parameters: |
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weight: 0.10 |
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density: 0.5 |
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merge_method: dare_ties |
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base_model: TareksLab/MO-MODEL6-V0.1-LLaMa-70B |
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parameters: |
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normalize: false |
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int8_mask: true |
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dtype: float32 |
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out_dtype: bfloat16 |
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chat_template: llama3 |
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tokenizer: |
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source: base |
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``` |
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