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za-ck's Projects

955.wlb icon 955.wlb

955 不加班的公司名单 - 工作 955,work–life balance (工作与生活的平衡)

ace icon ace

[ACL-IJCNLP 2021] Automated Concatenation of Embeddings for Structured Prediction

ailearning icon ailearning

AiLearning:数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

allennlp_tutorial icon allennlp_tutorial

Tutorial on how to use AllenNLP for sequence modeling (including hierarchical LSTMs and CRF decoding)

awesome-diffusion-models icon awesome-diffusion-models

A collection of resources and papers on Diffusion Models and Score-based Models, a darkhorse in the field of Generative Models

beautiful-jekyll icon beautiful-jekyll

✨ Build a beautiful and simple website in literally minutes. Demo at https://beautifuljekyll.com

bert-bilstm-crf-ner icon bert-bilstm-crf-ner

Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services

bert-ner icon bert-ner

Use Google's BERT for named entity recognition (CoNLL-2003 as the dataset).

chatgpt_academic icon chatgpt_academic

中科院科研工作专用ChatGPT,特别优化学术Paper润色体验,支持自定义快捷按钮,支持markdown表格显示,Tex公式双显示,代码显示功能完善,新增本地Python工程剖析功能/自我剖析功能

codeswitch icon codeswitch

CodeSwitch is a NLP tool, can use for language identification, pos tagging, name entity recognition, sentiment analysis of code mixed data.

cosda-ml icon cosda-ml

CoSDA-ML: Multi-Lingual Code-Switching Data Augmentation for Zero-Shot Cross-Lingual NLP

data-structres icon data-structres

浙江大学《数据结构》上课笔记 + 数据结构实现 + 课后题题解

dive-into-dl-pytorch icon dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

dive-into-dl-tensorflow2.0 icon dive-into-dl-tensorflow2.0

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现,项目已得到李沐老师的同意

dm-ticket icon dm-ticket

大麦网自动购票, 支持docker一键部署。https://t.me/+2EELgNTYiMYxMTFl

dpr icon dpr

Dense Passage Retriever - is a set of tools and models for open domain Q&A task.

entity-recognition-datasets icon entity-recognition-datasets

A collection of corpora for named entity recognition (NER) and entity recognition tasks. These annotated datasets cover a variety of languages, domains and entity types.

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