GeorgeVern/lmcor
Code for the EACL 2024 paper: "Small Language Models Improve Giants by Rewriting Their Outputs"
LM-Corrector helps improve the quality of text generated by large language models for tasks like summarization, translation, or grammatical error correction. It takes multiple text outputs from an existing LLM as input and then refines them into a single, higher-quality output. This tool is for AI researchers and practitioners who want to get better results from their language models.
No commits in the last 6 months.
Use this if you are using large language models for text generation tasks and want to significantly improve the accuracy and fluency of their outputs without retraining the original LLM.
Not ideal if you need a pre-trained, ready-to-use application, as this project requires technical setup and model training.
Stars
12
Forks
1
Language
Python
License
—
Category
Last pushed
Apr 20, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/GeorgeVern/lmcor"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
jncraton/languagemodels
Explore large language models in 512MB of RAM
microsoft/unilm
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
haizelabs/verdict
Inference-time scaling for LLMs-as-a-judge.
albertan017/LLM4Decompile
Reverse Engineering: Decompiling Binary Code with Large Language Models
bytedance/Sa2VA
Official Repo For Pixel-LLM Codebase