Alternatives and similar repositories for o1_inference_scaling_laws:

Users that are interested in o1_inference_scaling_laws are comparing it to the libraries listed below

• ucl-dark / llm_debate
  Code release for "Debating with More Persuasive LLMs Leads to More Truthful Answers"
  ☆104Updated last year
• hkust-nlp / llm-compression-intelligence
  Official github repo for the paper "Compression Represents Intelligence Linearly" [COLM 2024]
  ☆133Updated 7 months ago
• Yu-Fangxu / FoR
  [ICML 2025] Flow of Reasoning: Training LLMs for Divergent Problem Solving with Minimal Examples
  ☆85Updated last month
• architsharma97 / dpo-rlaif
  ☆97Updated 10 months ago
• casmlab / NPHardEval
  Repository for NPHardEval, a quantified-dynamic benchmark of LLMs
  ☆54Updated last year
• hkust-nlp / PreSelect
  ☆46Updated 2 months ago
• JacobPfau / fillerTokens
  ☆60Updated last year
• ScalingIntelligence / large_language_monkeys
  ☆91Updated 7 months ago
• SynthLabsAI / big-math
  A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models
  ☆51Updated 2 months ago
• hamishivi / automated-instruction-selection
  Exploration of automated dataset selection approaches at large scales.
  ☆39Updated 2 months ago
• da03 / Internalize_CoT_Step_by_Step
  ☆170Updated 2 weeks ago
• princeton-nlp / USACO
  Can Language Models Solve Olympiad Programming?
  ☆116Updated 3 months ago
• THUDM / T1
  Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling
  ☆101Updated 3 months ago
• jwhj / OREO
  ☆109Updated 3 months ago
• GAIR-NLP / AIME-Preview
  ☆62Updated last month
• ryoungj / ObsScaling
  [NeurIPS'24 Spotlight] Observational Scaling Laws
  ☆54Updated 7 months ago
• kanishkg / stream-of-search
  Repository for the paper Stream of Search: Learning to Search in Language
  ☆145Updated 3 months ago
• mnoukhov / async_rlhf
  Code and Configs for Asynchronous RLHF: Faster and More Efficient RL for Language Models
  ☆48Updated last week
• allenai / easy-to-hard-generalization
  Code for the arXiv preprint "The Unreasonable Effectiveness of Easy Training Data"
  ☆47Updated last year
• hkust-nlp / B-STaR
  B-STAR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
  ☆80Updated last month
• rmshin / llm-mcts
  ☆36Updated 10 months ago
• lmarena / PPE
  ☆45Updated last week
• martin-wey / CodeUltraFeedback
  CodeUltraFeedback: aligning large language models to coding preferences
  ☆71Updated 10 months ago
• SalesforceAIResearch / LaTRO
  ☆114Updated 2 months ago
• qishenghu / InstructCoder
  InstructCoder: Instruction Tuning Large Language Models for Code Editing | Oral ACL-2024 srw
  ☆59Updated 7 months ago
• protagolabs / odyssey-math
  ☆83Updated 3 months ago
• ars22 / scaling-LLM-math-synthetic-data
  Code and data used in the paper: "Training on Incorrect Synthetic Data via RL Scales LLM Math Reasoning Eight-Fold"
  ☆30Updated 10 months ago
• hamishivi / EasyLM
  Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Fl…
  ☆72Updated 8 months ago
• huggingface / ioi
  ☆34Updated last month
• IBM / SALMON
  Self-Alignment with Principle-Following Reward Models
  ☆160Updated last year