| 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-70b-v1.0 | |
| **aka MiquMaid-v1-70B + interleaved WinterGoddess-1.4x-70B-L2** | |
|  | |
| A [mergekit](https://github.com/arcee-ai/mergekit) frankenmerge based on [MiquMaid-v1-70B](https://huggingface.co/NeverSleep/MiquMaid-v1-70B) with interleaved layers of [Sao10K/WinterGoddess-1.4x-70B-L2](https://huggingface.co/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](https://huggingface.co/NeverSleep/MiquMaid-v1-70B) or [152334H/miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf) after 16k context. | |
| Layers: 136 | |
| ### License | |
| No license. Component models based on the [Mistral AI Miqu-1](https://huggingface.co/miqudev/miqu-1-70b/tree/main) 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 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. |