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README.md

@@ -8,12 +8,12 @@ tags:
 - mergekit
 - merge
 ---
-# aranea-ancilla-70b-v1.0
+# aranea-ancilla-116b-v1.0
 **aka MiquMaid-v1-70B + interleaved WinterGoddess-1.4x-70B-L2**
 
 ![image/png](https://huggingface.co/divinetaco/aranea-ancilla-116b-v1.0/resolve/main/aranea-ancilla.png)
 
-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).  
+A [mergekit](https://github.com/arcee-ai/mergekit) frankenmerge based on [NeverSleep/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.
@@ -33,7 +33,7 @@ No license. Component models based on the [Mistral AI Miqu-1](https://huggingfac
 ### 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.
+- 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