Model Breadcrumbs: Scaling Multi-Task Model Merging with Sparse Masks
Paper
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2312.06795
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Published
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1
This is a merge of pre-trained language models created using mergekit.
This model was merged using the Model Breadcrumbs merge method using TareksLab/Second-Dimension-V1-LLaMa-70B as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
- model: TareksLab/Sixth-Dimension-V1-LLaMa-70B
parameters:
weight: [0.1, 0.1, 0.1, 0.2, 0.5]
density: 0.9
gamma: 0.01
- model: TareksLab/Fifth-Dimension-V1-LLaMa-70B
parameters:
weight: [0.1, 0.1, 0.2, 0.4, 0.2]
density: 0.9
gamma: 0.01
- model: TareksLab/Zero-Dimension-F-LLaMa-70B
parameters:
weight: [0.1, 0.2, 0.4, 0.2, 0.1]
density: 0.9
gamma: 0.01
- model: TareksLab/Third-Dimension-V1-LLaMa-70B
parameters:
weight: [0.2, 0.4, 0.2, 0.1, 0.1]
density: 0.9
gamma: 0.01
- model: TareksLab/First-Dimension-V1-LLaMa-70B
parameters:
weight: [0.5, 0.2, 0.1, 0.1, 0.1]
density: 0.9
gamma: 0.01
merge_method: breadcrumbs
base_model: TareksLab/Second-Dimension-V1-LLaMa-70B
parameters:
normalize: false
lambda: 1.0
dtype: float32
out_dtype: bfloat16
chat_template: llama3
tokenizer:
source: TareksLab/Zero-Dimension-F-LLaMa-70B
pad_to_multiple_of: 8