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  ((MantiCore3E+VicunaCocktail)+[SuperCOT+[StorytellingV2+(SuperHOTProtoType-8192ctx+Metharme)]])
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  This model is the result of an experimental use of LoRAs on language models and model merges that are not the base HuggingFace-format LLaMA model they were intended for.
 
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- ## Experiment Purpose:
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- Outcomes of applying Lower Order Rank Adapters in unconventional ways.
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- Determine if applying LoRAs and stacking LoRAs onto merged models bypasses the zero-sum result of weight-sum model merging.
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- The desired result is to additively apply desired features without paradoxically watering down a model's effective behavior.
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- Results are very promising. Further tests are required.
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  Releasing Chimera as-is; Alpaca instruct verified working, Vicuna instruct formats should work.
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  If using KoboldAI or Text-Generation-WebUI, recommend switching between Godlike and Storywriter presets and adjusting output length + instructions in memory.
 
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  ((MantiCore3E+VicunaCocktail)+[SuperCOT+[StorytellingV2+(SuperHOTProtoType-8192ctx+Metharme)]])
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  This model is the result of an experimental use of LoRAs on language models and model merges that are not the base HuggingFace-format LLaMA model they were intended for.
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+ The desired outcome is to additively apply desired features without paradoxically watering down a model's effective behavior.
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+ Potential limitations - LoRAs applied on top of each other may intercompete.
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+ Subjective results are very promising. Further tests are required to include isolated tests and benchmarking (exact method not determined at this time).
 
 
 
 
 
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  Releasing Chimera as-is; Alpaca instruct verified working, Vicuna instruct formats should work.
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  If using KoboldAI or Text-Generation-WebUI, recommend switching between Godlike and Storywriter presets and adjusting output length + instructions in memory.