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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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# merged_model_output |
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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 [DELLA](https://arxiv.org/abs/2406.11617) merge method using /media/administrator/oiseauxai1data/modelout/Smart-base-v2 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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* /media/administrator/oiseauxai1data/modelout/Story-Base-V2 |
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* /media/administrator/oiseauxai1data/modelout/Middle-Base-V2 |
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* /media/administrator/oiseauxai1data/modelout/Dark-Base-V2 |
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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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# --- Mergekit Example: della_linear --- |
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# Method: Implements the DELLA concept (Deep Ensembling with Layer-wise Linear Averaging). |
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# This typically involves a sophisticated layer-wise linear combination of models. |
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base_model: /media/administrator/oiseauxai1data/modelout/Smart-base-v2 # The foundational model |
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models: |
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- model: /media/administrator/oiseauxai1data/modelout/Smart-base-v2 |
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parameters: |
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weight: [0.4, 0.2, 0.2, 0.2] # Contribution of this model (e.g., 50%) (can also use a gradiant) [0.1, 0.1, 0.1, 0.2, 0.5] |
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density: 0.50 # Sparsity/pruning factor for this model's contribution. |
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epsilon: 0.15 # Single epsilon for the pruning |
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models: |
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- model: /media/administrator/oiseauxai1data/modelout/Dark-Base-V2 |
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parameters: |
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weight: [0.1, 0.2, 0.3, 0.4] # Contribution of this model (e.g., 50%) (can also use a gradiant) [0.1, 0.1, 0.1, 0.2, 0.5] |
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density: 0.50 # Sparsity/pruning factor for this model's contribution. |
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epsilon: 0.15 # Single epsilon for the pruning |
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- model: /media/administrator/oiseauxai1data/modelout/Story-Base-V2 |
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parameters: |
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weight: [0.2, 0.3, 0.2, 0.3] # Contribution of this model (e.g., 50%) (can also use a gradiant) [0.1, 0.1, 0.1, 0.2, 0.5] |
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density: 0.50 # Sparsity/pruning factor for this model's contribution. |
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epsilon: 0.15 # Single epsilon for the pruning |
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- model: /media/administrator/oiseauxai1data/modelout/Middle-Base-V2 |
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parameters: |
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weight: [0.3, 0.3, 0.3, 0.1] # Contribution of this model (e.g., 50%) (can also use a gradiant) [0.1, 0.1, 0.1, 0.2, 0.5] |
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density: 0.50 # Sparsity/pruning factor for this model's contribution. |
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epsilon: 0.15 # Single epsilon for the pruning |
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model_name: L3.3-70B-Amalgamma-V8 # Name of your merge |
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dtype: float32 # Input size float32, float16, bfloat16 |
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out_dtype: bfloat16 # output size float32, float16, bfloat16 |
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merge_method: della |
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parameters: |
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normalize: false # If true (default), weights are normalized to sum to 1. |
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# If false, absolute weights are used. |
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lambda: 1.1 # Single lambda for scaling the final merged deltas |
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tokenizer_source: base # Or 'base' if base_model is set, or 'union', careful with this one |
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chat_template: llama3 # Template for chat (Chatml, llama3, etc...) |
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license: apache-2.0 # License type |
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``` |
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