Popular GitHub Repositories for Pre Trained Language Models

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

The official GitHub page for the survey paper "A Survey of Large Language Models".

Must-read papers on prompt-based tuning for pre-trained language models.

RoBERTa中文预训练模型: RoBERTa for Chinese

A curated list of NLP resources focused on Transformer networks, attention mechanism, GPT, BERT, ChatGPT, LLMs, and transfer learning.

Must-read Papers on Knowledge Editing for Large Language Models.

A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.

Awesome papers on Language-Model-as-a-Service (LMaaS)

Keyphrase or Keyword Extraction 基于预训练模型的中文关键词抽取方法（论文SIFRank: A New Baseline for Unsupervised Keyphrase Extraction Based on Pre-trained Language Model 的中文版代码）

A PyTorch-based model pruning toolkit for pre-trained language models

HugNLP is a unified and comprehensive NLP library based on HuggingFace Transformer. Please hugging for NLP now!? HugNLP will released to @HugAILab

The code of our paper "SIFRank: A New Baseline for Unsupervised Keyphrase Extraction Based on Pre-trained Language Model"

[ICLR 2023] Multimodal Analogical Reasoning over Knowledge Graphs

Must-read papers on improving efficiency for pre-trained language models.

The Paper List on Data Contamination for Large Language Models Evaluation.

We start a company-name recognition task with a small scale and low quality training data, then using skills to enhanced model training speed and predicting performance with least artificial participation. The methods we use involve lite pre-training models such as Albert-small or Electra-small with financial corpus, knowledge of distillation and multi-stage learning. The result is that we improve the recall rate of company names recognition task from 0.73 to 0.92 and get 4 times as fast as BERT-Bilstm-CRF model.

VaLM: Visually-augmented Language Modeling. ICLR 2023.

? 对Chinese-LLaMA-Alpaca进行使用说明和核心代码注解

ChatCell: Facilitating Single-Cell Analysis with Natural Language

[ACL'23] Open KG Completion with PLM (Bridging Text Mining and Prompt Engineering)