Name: duanzhihua
Type: User
Company: China Telecom Corporation Limited Shanghai Branch
Bio: I participated in many Spark books edited by Wang Jialin teacher:e.g. Spark big data business reality Trilogy 2020 Tsinghua University published
Location: Shanghai China
Blog: https://blog.csdn.net/duan_zhihua
duanzhihua's Projects
Awesome-LLM: a curated list of Large Language Model
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
A list of totally open alternatives to ChatGPT
白泽说人话,通万物之情,晓天下万物状貌。
CCF BDCI 2019 互联网新闻情感分析 复赛top1解决方案
美丽东自然语言处理百宝箱~命名实体识别,文本分类,语言模型,文本摘要。
BELLE: Be Everyone's Large Language model Engine(开源中文对话大模型)
This repository contains code to benchmark lookup table entity extraction.
TensorFlow code and pre-trained models for BERT
使用Bert,ERNIE,进行中文文本分类
BERT-DST: Scalable End-to-End Dialogue State Tracking with Bidirectional Encoder Representations from Transformer
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
bert for chinese text classification
Fine-grained Post-training for Improving Retrieval-based Dialogue Systems - NAACL 2021
Tool for visualizing BERT's self-attention layers
Low-cost Inference Package for Big Pretrained Language Models (PLMs)
Pre-trained subword embeddings in 275 languages, based on Byte-Pair Encoding (BPE)
learning
In Building Systems With The ChatGPT API, you will learn how to automate complex workflows using chain calls to a large language model.
一个可以自己进行训练的中文聊天机器人, 根据自己的语料训练出自己想要的聊天机器人,可以用于智能客服、在线问答、智能聊天等场景。
Chatbot which communicates with voice
A powerful dataset generator for Rasa NLU, inspired by Chatito
ChatGLM-6B:开源双语对话语言模型 | An Open Bilingual Dialogue Language Model
一种平价的chatgpt实现方案, 基于ChatGLM-6B + LoRA
Wechat robot based on ChatGPT, which using OpenAI api and itchat library. 使用ChatGPT搭建微信聊天机器人,基于GPT3.5 API和itchat实现
Jupyter code notebooks of "ChatGPT Prompt Engineering for Developers" by DeepLearning.AI and OpenAI.
The ChatGPT Retrieval Plugin lets you easily search and find personal or work documents by asking questions in everyday language.