transformers

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

CVPR 2023 论文和开源项目合集

👑 Easy-to-use and powerful NLP library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis and 🖼 Diffusion AIGC system etc.

An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

🔍 Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-3 and alike). Haystack offers production-ready tools to quickly build ChatGPT-like question answering, semantic search, text generation, and more.

💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

Plug and play modules to optimize the performances of your AI systems 🚀

A PyTorch-based Speech Toolkit

Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

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

Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). Technique was originally created by https://twitter.com/advadnoun

An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.

Leveraging BERT and c-TF-IDF to create easily interpretable topics.

This repository contains demos I made with the Transformers library by HuggingFace.

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

Transformers for Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI

State of the Art Natural Language Processing

中文语言理解测评基准 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard