A library for doing homomorphic encryption operations on tensors

A Toy Implementation in Python of [FV12]

Concrete: TFHE Compiler that converts python programs into FHE equivalent

Implementation for "AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification"

A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility

Code examples in pyTorch and Tensorflow for CS230

A framework for Privacy Preserving Machine Learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

Solution for Avito Duplicate Ads Detection competition

Example python package with pybind11 cpp extension

Repository for the paper "Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images"

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

DeepCT and HDCT uses BERT to generate novel, context-aware bag-of-words term weights for documents and queries.

Facilitating the design, comparison and sharing of deep text matching models.

Anserini notebooks

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…

YSDA course in Natural Language Processing

Course webpage for COMP 790, (Deep) Learning from Limited Labeled Data

Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀

Jupyter Notebooks with Deep Learning Tutorials

Perform data science on data that remains in someone else's server

Best Practices, code samples, and documentation for Computer Vision.

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

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

The Turing Change Point Dataset - A collection of time series for the evaluation and development of change point detection algorithms

🤗 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.