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Chimere Engram Tables
Pre-built N-gram hash tables for the Chimere multi-tier Engram memory system. These provide O(1) lookup for domain-specific token sequences, used to bias LLM generation with factual knowledge at the logit level.
Files
| File | Size | Domain | N-grams |
|---|---|---|---|
code.engr |
155 KB | Programming / software | Code patterns, API signatures |
cyber.engr |
172 KB | Cybersecurity | Threat indicators, CVE patterns |
general.engr |
679 KB | General knowledge | Common factual patterns |
Format
Binary hash tables with FNV-1a hashing, compatible with the Rust EngramLookup implementation in chimere-server and the Python tools in chimere-odo.
Structure
- 20-byte header (magic, version, n-gram count, table size)
- Hash table slots with FNV-1a keys
- O(1) lookup, <10ns with Cuckoo filter pre-screening
Usage
# Query an Engram table
python engram_query.py code.engr "async def main"
# Build your own from documents
python engram_ingest.py --input docs/ --output custom.engr
Author
Kevin Remondiere — Independent ML researcher
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