DELLA-Merging: Reducing Interference in Model Merging through Magnitude-Based Sampling
Paper
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2406.11617
•
Published
•
8
This is a merge of pre-trained language models created using mergekit.
This model was merged using the DELLA merge method using TareksLab/Scrivener-Base-V4-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/Wordsmith-V2.0-LLaMa-70B
parameters:
weight: 0.20
density: 0.5
epsilon: 0.05
lambda: 1.0
- model: TareksLab/Anathema-V2-LLaMA-70B
parameters:
weight: 0.20
density: 0.5
epsilon: 0.05
lambda: 1.0
- model: TareksLab/Scrivener-Base-V4-LLaMA-70B
parameters:
weight: 0.20
density: 0.5
epsilon: 0.05
lambda: 1.0
- model: TareksLab/RolePlayer-V4-LLaMa-70B
parameters:
weight: 0.20
density: 0.5
epsilon: 0.05
lambda: 1.0
- model: TareksLab/Erudite-V1-Unleashed-LLaMA-70B
parameters:
weight: 0.20
density: 0.5
epsilon: 0.05
lambda: 1.0
merge_method: della
base_model: TareksLab/Scrivener-Base-V4-LLaMA-70B
parameters:
normalize: false
int8_mask: true
dtype: bfloat16
chat_template: llama3
tokenizer:
source: TareksLab/Scrivener-Base-V4-LLaMA-70B