genpark-prompt-token-length-budget-packager-skill
mcp
Warn
Health Warn
- No license — Repository has no license file
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Low visibility — Only 7 GitHub stars
Code Pass
- Code scan — Scanned 6 files during light audit, no dangerous patterns found
Permissions Pass
- Permissions — No dangerous permissions requested
No AI report is available for this listing yet.
Bin-packing optimizer grouping variable-length training examples into fixed context window token budgets
README.md
genpark-prompt-token-length-budget-packager-skill
A First-Fit Decreasing (FFD) bin packing optimizer designed to maximize context window utilization during LLM fine-tuning and batch inference.
Architecture
flowchart TD
Examples[Variable Length Prompts] --> Estimator[Token Length Estimator]
Estimator --> Sorter[Descending Length Sorter]
Sorter --> FFD[First-Fit Decreasing Packer]
FFD --> Bins[Optimized Fixed-Budget Context Bins]
Features
- FFD Bin Packing: Minimizes padding waste across fixed token windows (2k, 4k, 8k, 32k).
- Utilization Analytics: Calculates utilization rate and token waste per bin.
- Pure Python Standard Library: No external dependencies.
Reviews (0)
Sign in to leave a review.
Leave a reviewNo results found