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#

gpt2

Here are 458 public repositories matching this topic...

bertviz

BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

  • UpdatedJun 1, 2025
  • Python

中文nlp解决方案(大模型、数据、模型、训练、推理)

  • UpdatedAug 5, 2025
  • Jupyter Notebook

GPT2 for Chinese chitchat/用于中文闲聊的GPT2模型(实现了DialoGPT的MMI思想)

  • UpdatedOct 30, 2023
  • Python

RoBERTa中文预训练模型: RoBERTa for Chinese

  • UpdatedJul 22, 2024
  • Python

a fast and user-friendly runtime for transformer inference (Bert, Albert, GPT2, Decoders, etc) on CPU and GPU.

  • UpdatedJul 18, 2025
  • C++

Human ChatGPT Comparison Corpus (HC3), Detectors, and more! 🔥

  • UpdatedDec 1, 2023
  • Python

pytorch实现 Bert 做seq2seq任务,使用unilm方案,现在也可以做自动摘要,文本分类,情感分析,NER,词性标注等任务,支持t5模型,支持GPT2进行文章续写。

  • UpdatedJun 18, 2022
  • Python

Chinese NewsTitle Generation Project by GPT2.带有超级详细注释的中文GPT2新闻标题生成项目。

  • UpdatedMar 8, 2022
  • Python

Simple Text-Generator with OpenAI gpt-2 Pytorch Implementation

  • UpdatedJul 8, 2019
  • Python

TextGen: Implementation of Text Generation models, include LLaMA, BLOOM, GPT2, BART, T5, SongNet and so on. 文本生成模型,实现了包括LLaMA,ChatGLM,BLOOM,GPT2,Seq2Seq,BART,T5,UDA等模型的训练和预测,开箱即用。

  • UpdatedSep 14, 2024
  • Python
arabert

Pre-trained Transformers for Arabic Language Understanding and Generation (Arabic BERT, Arabic GPT2, Arabic ELECTRA)

  • UpdatedOct 17, 2022
  • Python
GraphWaveletNeuralNetwork

NLP 领域常见任务的实现,包括新词发现、以及基于pytorch的词向量、中文文本分类、实体识别、摘要文本生成、句子相似度判断、三元组抽取、预训练模型等。

  • UpdatedMay 20, 2023
  • Python

Easy-to-use CPM for Chinese text generation(基于CPM的中文文本生成)

  • UpdatedApr 10, 2023
  • Python

Guide: Finetune GPT2-XL (1.5 Billion Parameters) and finetune GPT-NEO (2.7 B) on a single GPU with Huggingface Transformers using DeepSpeed

  • UpdatedJun 14, 2023
  • Python

One-click training of your own GPT. Training a GPT has never been easier for beginners. / 一键从头训练一个LLM,0基础训练GPT原来可以这么简单?

  • UpdatedNov 12, 2025
  • Python

PyTorch Implementation of OpenAI GPT-2

  • UpdatedJul 4, 2024
  • Python

1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and GraphSAGE based on message passing.

  • UpdatedAug 14, 2024
  • Python

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