Model Overview

alnrg2arg/test_wanda_240109 is a 10.7 billion parameter language model derived from a pruning process applied to the alnrg2arg/test model. It integrates characteristics from two base models: jeonsworld/CarbonVillain-en-10.7B-v2 and kyujinpy/Sakura-SOLAR-Instruct-DPO-v2.

Key Characteristics

• Parameter Count: 10.7 billion parameters.
• Sparsity: The model exhibits a sparsity of 0.49, indicating that a significant portion of its parameters have been pruned. This often leads to reduced memory footprint and faster inference times compared to its dense counterparts, while aiming to retain performance.
• Base Models: Built upon two distinct base models, suggesting a potential blend of their respective strengths and capabilities.

Good For

This model is suitable for users looking for a language model with a moderate parameter count that might offer efficiency benefits due to its pruned nature. Its foundation on established base models suggests applicability across a range of general language understanding and generation tasks.