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This is the official implementation of Graph of Thoughts: Solving Elaborate Problems with Large Language Models. This framework gives you the ability to solve complex problems by modeling them as a Graph of Operations (GoO), which is automatically executed with a Large Language Model (LLM) as…
The main features of spcl/graph-of-thoughts are: Reasoning Frameworks, Single Agent Optimization.
Projects with overlapping indexed features include: princeton-nlp/tree-of-thought-llm — Note: https://github.com/kyegomez/tree-of-thoughts CANNOT replicate paper results. amazon-science/auto-cot — Cheer AI up with the "let's think step by step" prompt? More plz. Let’s think not just step by step, but also one by… chengpengli1003/cort. chengsong-huang/r-zero — Check out our paper or webpage for the details. craftjarvis/jarvis-1 — [[Website]](http://craftjarvis-jarvis1.github.io/) [[Paper]](https://arxiv.org/abs/2311.05997)… allenai/open-instruct — Open-Instruct is a distributed training and instruction tuning framework for large language models. It functions as a…
Note: https://github.com/kyegomez/tree-of-thoughts CANNOT replicate paper results.
Cheer AI up with the "let's think step by step" prompt? More plz. Let’s think not just step by step, but also one by one.
Open-Instruct is a distributed training and instruction tuning framework for large language models. It functions as a coordinator for supervised fine-tuning, reinforcement learning from human feedback pipelines, and tool-use training, providing specialized roles for dataset curation and model alignment. The project distinguishes itself through a high-performance training architecture that utilizes actor-based distributed coordination and hybrid sharding to manage large GPU clusters. It implements advanced alignment techniques including direct preference optimization, group relative policy opt
