Resolving Interference When Merging Models
Paper
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2306.01708
•
Published
•
15
This model turned out really well, intelligent, knowledgeable, and of course state-of-the-art Uncensored performance.
Please use responsibly, or at least discretely.
This model will help you do anything and everything you probably shouldn't be doing.
As of this writing, this model tops the UGI Leaderboard for models under 70 billion parameters in both the UGI and W10 categories.
This is a merge of pre-trained language models created using mergekit.
This model was merged using the TIES merge method using darkc0de/XortronCriminalComputing as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
- model: darkc0de/XortronCriminalComputing
- model: TroyDoesAI/BlackSheep-24B
parameters:
density: 0.8
weight: 0.8
merge_method: ties
base_model: darkc0de/XortronCriminalComputing
dtype: float16
Base model
darkc0de/XortronCriminalComputingConfig