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Neural Mesh extends the concept of Mixture of Experts by allowing bidirectional expert communication.
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The experts are shared in a bidimensional grid (2x2, 4x4, etc.) layout, that allows for them to communicate with their neighbors using the "Neighbor Exchange" method.
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Just like MoE models, Mesh models have dynamic routing, and through the routing_k parameter you can define the amount of active parameters. For this model (2x2):
- top-1 routing: 173M active parameters
- top-2 routing: 242M active parameters (default)
- dense routing: 302M active parameters
This small language model is just a proof-of-concept, paving the way to the final release, which is likely to happen in Q4 2025, and include more models and better support from external libraries such as Transformers and Llama.cpp.