aurekai/model-memory

Public model memory archive for the Aurekai platform. Stores compiled model representations, SAE dictionaries, and semantic embeddings for zero-shot operational orchestration.

Overview

Model memory serves as the central knowledge base for Aurekai's runtime, enabling semantic querying and model-based decision making. This repository hosts:

• Compiled Model Binaries: Pre-compiled Aurekai model representations (.akmodel, .bfmodel)
• SAE Dictionaries: Sparse autoencoder dictionaries for model interpretability (.aksae, .bfsae)
• Semantic Embeddings: Cached embeddings for fast semantic search across operators
• Manifest Metadata: Aurekai and legacy Bonfyre format manifests

Quick Start

# Download latest model memory archive
curl -L https://huggingface.co/aurekai/model-memory/resolve/main/aurekai-model-memory-qwen3-8b-20260502.tar.gz -o model-memory.tar.gz

# Extract
tar -xzf model-memory.tar.gz

# Use with Aurekai runtime
export AUREKAI_MODEL_MEMORY=$(pwd)/model-memory
akai run <recipe> --model-cache --semantic-search

Format Specifications

Aurekai First Formats (.ak*)

• .akmodel: Aurekai-native model compiled format

  • Used by Aurekai runtime for direct inference
  • Optimized for semantic routing and operator selection

• .aksae: Aurekai-native SAE dictionary format

  • Sparse autoencoder coefficients in Aurekai serialization
  • Default SAE for model interpretability

• .akfpqx: Aurekai-native FPQx alignment format

  • Feature-to-proxy quantization alignments
  • Model-to-model alignment data

Legacy Bonfyre Formats (.bf*)

For backward compatibility, this repository includes legacy Bonfyre format equivalents:

• .bfmodel → Bonfyre binary model representation
• .bfsae → Bonfyre SAE dictionary format
• .bffpqx → Bonfyre FPQx alignment format

Available Models

Qwen3 8B (qwen3-8b)

• Release: 2026-05-02
• Archive: aurekai-model-memory-qwen3-8b-20260502.tar.gz
• Size: See SHA256SUMS
• Formats:
  • qwen3-8b.akmodel + qwen3-8b.bfmodel
  • default.aksae + default.bfsae
  • qwen3-to-llama3.akfpqx + qwen3-to-llama3.bffpqx

Integration with Aurekai

Environment Variables

export AUREKAI_MODEL_MEMORY=/path/to/model-memory
export AUREKAI_SAE_DEFAULT=model-memory/default.aksae
export AUREKAI_EMBEDDINGS_CACHE=/tmp/aurekai-embeddings

In Aurekai Config

{
  "model_memory": {
    "path": "./model-memory",
    "formats": ["akmodel", "bfmodel"],
    "sae_dicts": ["default.aksae", "default.bfsae"],
    "fpqx_alignments": ["qwen3-to-llama3.akfpqx"]
  }
}

Manifests

• aurekai.manifest.json: Aurekai public manifest with SAE and FPQx inventory
• bonfyre.manifest.json: Legacy Bonfyre manifest for backward compatibility

Both manifests are included in each release and describe:

• Available models and their paths
• SAE dictionary mappings (Aurekai → Legacy)
• FPQx alignment pairs for cross-model translation
• Operator compatibility and runtime requirements

Performance Notes

• Model memory archives are compressed with both gzip and zstd
• Use .tar.zst for faster decompression on supported systems
• Recommended extraction to SSD for optimal semantic search performance

License

Licensed under the Aurekai Open Source License. See LICENSE in the main Aurekai repository.

Related

• Main Aurekai Repo: https://github.com/aurekai/aurekai
• SAE Dictionaries: https://huggingface.co/aurekai/sae-dictionaries
• FPQx Alignments: https://huggingface.co/aurekai/fpqx-alignments
• Semantic Cache Benchmarks: https://huggingface.co/aurekai/semantic-cache-bench

Support

For issues or questions:

• GitHub Discussions: https://github.com/aurekai/aurekai/discussions
• GitHub Issues: https://github.com/aurekai/aurekai/issues