Pytorch implementation of "A Deep Reinforced Model for Abstractive Summarization" paper and pointer generator network
-
Updated
Oct 1, 2019 - Python
Pytorch implementation of "A Deep Reinforced Model for Abstractive Summarization" paper and pointer generator network
An easy python package to run quick basic QA evaluations. This package includes standardized QA evaluation metrics and semantic evaluation metrics: Black-box and Open-Source large language model prompting and evaluation, exact match, F1 Score, PEDANT semantic match, transformer match. Our package also supports prompting OPENAI and Anthropic API.
Simulator for training and evaluation of Recommender Systems
grpo to train long form QA and instructions with long-form reward model
The official PyTorch implementation for the Guided by Gut: Efficient Test-Time Scaling with Reinforced Intrinsic Confidence
Deep Reinforced Model for Abstractive Summarization
Add a description, image, and links to the rl-training topic page so that developers can more easily learn about it.
To associate your repository with the rl-training topic, visit your repo's landing page and select "manage topics."