File size: 3,952 Bytes
c35e874 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 | # 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
```bash
# 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](./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
```bash
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
```json
{
"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](https://github.com/aurekai/aurekai/blob/main/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
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