natural-language-processing
Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. More modern techniques, such as deep learning, have produced results in the fields of language modeling, parsing, and natural-language tasks.
Repositories (1431)
Tencent Pre-training framework in PyTorch & Pre-trained Model Zoo
The most accurate natural language detection library for Rust, suitable for short text and mixed-language text
Curated List: Practical Natural Language Processing done in Ruby
:helicopter: 保险行业语料库，聊天机器人
📖 Paper reading list in conversational AI.
Lightweight, useful implementation of conformal prediction on real data.
A powerful Swift framework for evaluating natural language math expressions
This Word Does Not Exist
A collection of notebooks for Natural Language Processing from NLP Town
Simple Text-Generator with OpenAI gpt-2 Pytorch Implementation
A central, open resource for data and tools related to chain-of-thought reasoning in large language models. Developed @ Samwald research group: https:...
Summarization Papers
🧹 Python package for text cleaning
Awesome-llm-role-playing-with-persona: a curated list of resources for large language models for role-playing with assigned personas
[ACL 2023] Reasoning with Language Model Prompting: A Survey
Unsupervised text tokenizer focused on computational efficiency
A curated list of awesome awesomeness about artificial intelligence
Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A
Pretrained model hub for Keras 3.
[ACL2023] We introduce LLM-Blender, an innovative ensembling framework to attain consistently superior performance by leveraging the diverse strengths...
A tool for learning vector representations of words and entities from Wikipedia
Official implementation of the papers "GECToR – Grammatical Error Correction: Tag, Not Rewrite" (BEA-20) and "Text Simplification by Tagging" (BEA-21)
Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning, training, and prompt engineering examples. A bonus secti...
A simple resume parser used for extracting information from resumes
A curated list of resources dedicated to Python libraries, LLMs, dictionaries, and corpora of NLP for Japanese
Source code for end-to-end dialogue model from the MultiWOZ paper (Budzianowski et al. 2018, EMNLP)
A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.
Machine Learning Open Source University
Learn about Machine Learning and Artificial Intelligence
Quiz & Assignment of Coursera
skweak: A software toolkit for weak supervision applied to NLP tasks
FacTool: Factuality Detection in Generative AI
Jcseg is a light weight NLP framework developed with Java. Provide CJK and English segmentation based on MMSEG algorithm, With also keywords extractio...
😇A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc
MindSpore + 🤗Huggingface: Run any Transformers/Diffusers model on MindSpore with seamless compatibility and acceleration.
[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
Processed / Cleaned Data for Paper Copilot
BookNLP, a natural language processing pipeline for books
A curated collection of iOS, ML, AR resources sprinkled with some UI additions
TextGAN is a PyTorch framework for Generative Adversarial Networks (GANs) based text generation models.
High-accuracy NLP parser with models for 11 languages.
A list of recent papers about Graph Neural Network methods applied in NLP areas.
Elasticsearch with BERT for advanced document search.
A CS degree with a focus on full-stack ML engineering, 2020
CALVIN - A benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks
All the slides, accompanying code and exercises all stored in this repo. 🎈
📚 Process PDFs, Word documents and more with spaCy
An R package for the Quantitative Analysis of Textual Data
Active learning for systematic reviews
Fast vectorization, topic modeling, distances and GloVe word embeddings in R.