hughbzhang / o1_inference_scaling_lawsLinks
Replicating O1 inference-time scaling laws
☆87Updated 6 months ago
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
Sorting:
- ☆97Updated 11 months ago
- [ICML 2025] Flow of Reasoning: Training LLMs for Divergent Reasoning with Minimal Examples☆93Updated 2 weeks ago
- A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models☆57Updated 3 months ago
- ☆35Updated 2 months ago
- Official github repo for the paper "Compression Represents Intelligence Linearly" [COLM 2024]☆138Updated 9 months ago
- Repository for NPHardEval, a quantified-dynamic benchmark of LLMs☆54Updated last year
- ☆68Updated 3 months ago
- ☆115Updated 4 months ago
- Exploration of automated dataset selection approaches at large scales.☆44Updated 3 months ago
- Critique-out-Loud Reward Models☆66Updated 8 months ago
- ☆78Updated last month
- ☆48Updated last month
- ☆65Updated last year
- Language models scale reliably with over-training and on downstream tasks☆97Updated last year
- Code for "Critique Fine-Tuning: Learning to Critique is More Effective than Learning to Imitate"☆157Updated 2 weeks ago
- [ICML 2025] Predictive Data Selection: The Data That Predicts Is the Data That Teaches☆47Updated 3 months ago
- PyTorch library for Active Fine-Tuning☆80Updated 4 months ago
- Can Language Models Solve Olympiad Programming?☆116Updated 5 months ago
- Implementation of the Quiet-STAR paper (https://arxiv.org/pdf/2403.09629.pdf)☆54Updated 10 months ago
- Long Context Extension and Generalization in LLMs☆57Updated 9 months ago
- Revisiting Mid-training in the Era of RL Scaling☆56Updated last month
- ☆180Updated 2 months ago
- [NeurIPS 2024] Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study☆51Updated 6 months ago
- Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Fl…☆75Updated 10 months ago
- Code for the arXiv preprint "The Unreasonable Effectiveness of Easy Training Data"☆48Updated last year
- Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision☆120Updated 9 months ago
- Stanford NLP Python library for benchmarking the utility of LLM interpretability methods☆95Updated 2 weeks ago
- ☆41Updated last year
- Code release for "Debating with More Persuasive LLMs Leads to More Truthful Answers"☆108Updated last year
- [ICML 2025] Teaching Language Models to Critique via Reinforcement Learning☆98Updated last month