DELLA-Merging: Reducing Interference in Model Merging through Magnitude-Based Sampling
Paper
• 2406.11617 • Published
• 10
This is a merge of pre-trained language models created using mergekit.
This model was merged using the Linear DELLA merge method using nbeerbower/Llama-3.1-Nemotron-lorablated-70B as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
- model: nbeerbower/llama3.1-kartoffeldes-70B
parameters:
weight: 0.20
density: 0.7
epsilon: 0.2
lambda: 1.1
- model: huihui-ai/DeepSeek-R1-Distill-Llama-70B-abliterated
parameters:
weight: 0.20
density: 0.7
epsilon: 0.2
lambda: 1.1
- model: TheDrummer/Anubis-70B-v1
parameters:
weight: 0.20
density: 0.7
epsilon: 0.2
lambda: 1.1
- model: ArliAI/Llama-3.3-70B-ArliAI-RPMax-v1.4
parameters:
weight: 0.20
density: 0.7
epsilon: 0.2
lambda: 1.1
- model: nbeerbower/Llama-3.1-Nemotron-lorablated-70B
parameters:
weight: 0.20
density: 0.7
epsilon: 0.1
lambda: 1.0
merge_method: della_linear
base_model: nbeerbower/Llama-3.1-Nemotron-lorablated-70B
parameters:
normalize: false
int8_mask: true
dtype: float32
out_dtype: bfloat16
chat_template: llama3
tokenizer:
source: nbeerbower/llama3.1-kartoffeldes-70B
pad_to_multiple_of: 8