base_model:
- 152334H/miqu-1-70b-sf
- NeverSleep/MiquMaid-v1-70B
- Sao10K/WinterGoddess-1.4x-70B-L2
library_name: transformers
tags:
- mergekit
- merge
aranea-ancilla-116b-v1.0
aka MiquMaid-v1-70B + interleaved WinterGoddess-1.4x-70B-L2
A mergekit frankenmerge based on NeverSleep/MiquMaid-v1-70B with interleaved layers of Sao10K/WinterGoddess-1.4x-70B-L2.
This was the top performing model from a series of merge experiments to create a highly coherant creative writing model.
Tests consisted of a series of private benchmarks and manual comparisons. A number of different base models, interleave models and layer offsets were compared.
- Usable context ~32768
- Recommended context ~16384
Non frankenstein miqu-1 finetunes generally outperform their frankenstein counterparts at very long contexts due to coherency loss.
As a rough suggestion I might suggest swapping out to either NeverSleep/MiquMaid-v1-70B or 152334H/miqu-1-70b-sf after 16k context.
Layers: 136
License
No license. Component models based on the Mistral AI Miqu-1 llama2 finetune that was released without license.
Interesting observations from benchmarking
- 10 layer interleave stride with a 20 layer interleave width consistently outperformed alternatives combinations.
- Offsetting the interleaved model's first set of layers generally improved coherency. [14-30] reliably beat the [10-30] mergekit slice configuration for various combinations of models.
- Quality of resulting merges can vary wildly. Whilst a merge of two strong models tends to produce a strong frankenstein model, this rule does not always hold true.
Quantizations
Exllamav2 quants will be available when bandwidth permits.