For installation instructions, model weights, and community support, visit the official AIRevolution repository (GitHub: akaime/airevolution). Standard open-source license (Apache 2.0) applies.
In the era of trillion-parameter behemoths, true revolution may not come from bigger models, but from smaller, smarter, and more private iterations—version by version, commit by commit. AIRevolution -v0.3.5- -Akaime-
Crucially, Akaime also introduced a novel , allowing the model to maintain long-term user-specific context across restarts—a feature typically reserved for cloud-based services. This is stored locally in a memory-mapped format, making it both private and persistent. Technical Deep Dive: What’s Inside v0.3.5? | Feature | Specification | |---------|----------------| | Base architecture | Transformer++ with sliding window attention | | Active parameters | 7B (dense) / 13B (MoE variant) | | Context window | 256k (theoretical), 200k (practical) | | Quantization support | FP16, INT8, INT4, and Akaime’s custom “Q4-K” | | Inference engine | MLX (Mac), CUDA (Nvidia), Vulkan (cross-platform) | | Plugin system | Python-based tool-use with sandboxing | Crucially, Akaime also introduced a novel , allowing
