knifeayumu/Cydonia-v4-MS3.2-Magnum-Diamond-24B
Cydonia-v4-MS3.2-Magnum-Diamond-24B is a 24 billion parameter language model developed by knifeayumu, created through a SLERP merge of TheDrummer/Cydonia-24B-v4 and Doctor-Shotgun/MS3.2-24B-Magnum-Diamond. This model aims to refine the behavior of its constituents, specifically addressing verbosity and 'horniness' observed in MS3.2-24B-Magnum-Diamond. It is designed for general language generation tasks, offering a balanced output by combining characteristics of its merged components.
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Overview
Cydonia-v4-MS3.2-Magnum-Diamond-24B is a 24 billion parameter language model developed by knifeayumu. It is a merged model, combining the strengths of two pre-trained language models: TheDrummer/Cydonia-24B-v4 and Doctor-Shotgun/MS3.2-24B-Magnum-Diamond. The merge was performed using the SLERP (Spherical Linear Interpolation) method, a technique often used to combine model weights smoothly.
Key Characteristics
- Parameter Count: 24 billion parameters.
- Merge Method: Utilizes the SLERP merge method for combining model weights.
- Base Model:
TheDrummer/Cydonia-24B-v4served as the base model for the merge. - Refinement Focus: The primary motivation for this merge was to mitigate the "horny and verbose" tendencies observed in the
Doctor-Shotgun/MS3.2-24B-Magnum-Diamondcomponent, aiming for more balanced and controlled output.
Intended Use Cases
This model is suitable for general language generation tasks where a refined and less verbose output is desired compared to its more uninhibited constituent models. It aims to provide a more tempered response profile, making it potentially useful for applications requiring more neutral or controlled text generation.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.