ladder-ai 0.1.9

Ladder + TTFT LLM Finetuning

Ladder + TTFT

Custom Ladder implementation on any Complex problem for LLM. a reimplementation of the paper “LADDER: SELF-IMPROVING LLMS THROUGH RECURSIVE PROBLEM DECOMPOSITION” https://arxiv.org/pdf/2503.00735

Finetuned Qwen2-0.5B with Ladder (Model Response)

setup

install from source using PDM

git clone [e-mail]:AbdelrahmanAbounida/ladder.git
cd ladder
pdm install

Run

our main usecase (Graph problem)

python src/main.py

TODO

Dataset Generation

• LLM Intelligence ratio Equation
• Custom Verification Method if required (for our Graph Usecase)
• DatasetGenerator > Generate subproblems according to the model intelligence ratio (step3)
• Difficulty Engine should decide the level of difficulty to be generated and what transformations to be applied
• Verification engine should use the small llm to be tuned not the Larger one
• LLM Engine (temperature cycling and persona based prompts for different operations like variant generation)

Ladder

• Ladder Finetuning Process
• GRPO Implementation
• reward functions

TTRL

• TTRL Implementation
• Data Generation in a loop

Others

• General Configurations for all Constants and Hyper Parameters
• implement different interfaced for different models to be used (HF, Ollama, VLLM, deepspeed, LiteLLM,..)
• LLMS Benchmarking
• Metrics and other evaluation methods
• implement more usecases if required for diverse benchmarking
• use accelerate / PEFT / deepspeed and vllm to speed up training process

Production

• Documentation
• packaging
• CICD
• Testing