grimjim/Magnolia-v1-Gemma2-8k-9B
Magnolia-v1-Gemma2-8k-9B by grimjim is a 9 billion parameter language model with a 16384-token context length, created by merging Delta-Vector/Odin-9B and anthracite-org/magnum-v3-9b-chatml using the SLERP method. This model exhibits variable text generation length and high creativity, though attention and safety aspects are noted as areas for potential improvement. It is intended as a merge contribution, offering a unique blend of its constituent models' characteristics.
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Overview
Magnolia-v1-Gemma2-8k-9B is a 9 billion parameter language model developed by grimjim, created through a merge of existing pre-trained models. It leverages the SLERP (Spherical Linear Interpolation) merge method to combine the characteristics of its base models, Delta-Vector/Odin-9B and anthracite-org/magnum-v3-9b-chatml. The model supports a substantial context length of 16384 tokens.
Key Capabilities
- Merged Architecture: Combines two distinct models, Odin-9B and magnum-v3-9b-chatml, potentially inheriting a blend of their strengths.
- Creative Text Generation: Noted for its "wild side" creativity in text output.
- Extended Context Window: Features a 16384-token context length, allowing for processing longer inputs and generating more coherent extended responses.
Good For
- Experimental Merging: Useful for researchers and developers interested in exploring the outcomes of model merging techniques, specifically SLERP.
- Creative Applications: Its high creativity might be beneficial for tasks requiring imaginative text generation, such as storytelling or brainstorming.
- Contribution to Merge Research: Positioned as a merge contribution, it can serve as a base for further experimentation or analysis within the model merging community.