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
Awesome-llm-role-playing-with-persona: a curated list of resources for large language models for role-playing with assigned personas
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:...
🧹 Python package for text cleaning
Summarization Papers
[ACL 2023] Reasoning with Language Model Prompting: A Survey
A curated list of awesome awesomeness about artificial intelligence
Unsupervised text tokenizer focused on computational efficiency
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
Processed / Cleaned Data for Paper Copilot
MindSpore + 🤗Huggingface: Run any Transformers/Diffusers model on MindSpore with seamless compatibility and acceleration.
[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
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.
All the slides, accompanying code and exercises all stored in this repo. 🎈
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
📚 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.