Stars
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Models and examples built with TensorFlow
Streamlit — A faster way to build and share data apps.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Write scalable load tests in plain Python 🚗💨
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
State-of-the-Art Text Embeddings
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
A library of extension and helper modules for Python's data analysis and machine learning libraries.
A Python library to access Instagram's private API.
Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
Keep track of internships for Summer 2020 for undergraduates interested in tech./SWE/related fields
Send WhatsApp message at certain time and many other things.
Stanford NLP Python library for Representation Finetuning (ReFT)
Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.
🚀 State-of-the-art parsers for natural language.
Parallelformers: An Efficient Model Parallelization Toolkit for Deployment
Implementations for a family of attention mechanisms, suitable for all kinds of natural language processing tasks and compatible with TensorFlow 2.0 and Keras.
Indonesian stemmer. Python port of PHP Sastrawi project.
Transformer-based image captioning extension for pytorch/fairseq
💳 Detecting the National Identification Cards with Deep Learning (Faster R-CNN)
⚛️ It is keras based implementation of siamese architecture using lstm encoders to compute text similarity
Segmentation of ID Cards using Semantic Segmentation
PyTorch Implementation of Knowing When to Look: Adaptive Attention via a Visual Sentinal for Image Captioning