waelantar/ATTS_Complete_Free_Package
ATTS: Adaptive Test-Time Scaling - A validated framework for optimizing LLM inference compute through difficulty-adaptive scaling. Achieves 28% token savings with only 2% accuracy cost. Implements 6-stage pipeline: difficulty estimation, mode selection, solution generation, USVA verification, escalation, and refinement.
Stars
1
Forks
—
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 08, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/llm-tools/waelantar/ATTS_Complete_Free_Package"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
LLM-Tuning-Safety/LLMs-Finetuning-Safety
We jailbreak GPT-3.5 Turbo’s safety guardrails by fine-tuning it on only 10 adversarially...
kyegomez/Sophia
Effortless plugin and play Optimizer to cut model training costs by 50%. New optimizer that is...
uthmandevsec/Self-Distillation
🤖 Enable continual learning by reproducing the On-Policy Self-Distillation algorithm for robust...
appier-research/robust-llm-finetunes
Accepted to NeurIPS 2025
jmcentire/apprentice
Train cheap models on expensive ones. Automatically. With receipts.