Search Results for author:
Found 4 papers, 0 papers with code
Stable Code Technical Report
Stable Code Instruct also exhibits state-of-the-art performance on the MT-Bench coding tasks and on Multi-PL completion compared to other instruction tuned models.
Teaching Large Language Models to Reason with Reinforcement Learning
Surprisingly, we find the sample complexity of Expert Iteration is similar to that of PPO, requiring at most on the order of $10^6$ samples to converge from a pretrained checkpoint.
Stable LM 2 1.6B Technical Report
We introduce StableLM 2 1. 6B, the first in a new generation of our language model series.
GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements
Outcome-based Reward Models (\textbf{ORMs}), trained to predict correctness of the final answer indicating when to refine, offer one convenient solution for deciding when to refine.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
