DELLA-Merging: Reducing Interference in Model Merging through Magnitude-Based Sampling
Paper
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2406.11617
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Published
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8
Trying to introduce thinking to Progenitor, but I need to play with it more I am not happy with it.
This is a merge of pre-trained language models created using mergekit.
This model was merged using the DELLA merge method using Tarek07/Experimental-Base-V2-R1-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: Sao10K/L3.1-70B-Hanami-x1
parameters:
weight: 0.20
density: 0.7
- model: Sao10K/70B-L3.3-Cirrus-x1
parameters:
weight: 0.20
density: 0.7
- model: SicariusSicariiStuff/Negative_LLAMA_70B
parameters:
weight: 0.20
density: 0.7
- model: TheDrummer/Anubis-70B-v1
parameters:
weight: 0.20
density: 0.7
- model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
parameters:
weight: 0.20
density: 0.7
merge_method: della
base_model: Tarek07/Experimental-Base-V2-R1-LLaMa-70B
parameters:
epsilon: 0.15
lambda: 1.1
int8_mask: true
out_dtype: bfloat16
tokenizer:
source: SicariusSicariiStuff/Negative_LLAMA_70B