There are 8 repositories under pre-trained-language-models topic.
中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)
An Open-Source Framework for Prompt-Learning.
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.
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
A Curated List of Language Models in Scientific Domains
Must-read papers on improving efficiency for pre-trained language models.
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.
[ICLR 2023] Multimodal Analogical Reasoning over Knowledge Graphs
📔 对Chinese-LLaMA-Alpaca进行使用说明和核心代码注解
The Paper List on Data Contamination for Large Language Models Evaluation.
PLM 기반 한국어 개체명 인식 (NER)
SIGIR'22 paper: Axiomatically Regularized Pre-training for Ad hoc Search
The official GitHub page for the survey paper "A Survey on Large Language Models: Applications, Challenges, Limitations, and Practical Usage".
Calculating FLOPs of Pre-trained Models in NLP
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization (ACL 2021)
[EMNLP 2023] Knowledge Rumination for Pre-trained Language Models
Seed-Guided Topic Discovery with Out-of-Vocabulary Seeds (NAACL'22)