natuan

QuantumGNN_molecules

Quantum graph neural network (quantum GNN) for molecular property prediction.

seizure

Epileptic seizure detection using auto-encoded features

bert

TensorFlow code and pre-trained models for BERT

bert-as-service

Mapping a variable-length sentence to a fixed-length vector using BERT model

bert-prune

BERT-Tickets

[NeurIPS 2020] "The Lottery Ticket Hypothesis for Pre-trained BERT Networks", Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin

cuad

CUAD (NeurIPS 2021)

finetune

Scikit-learn style model finetuning for NLP

gptq

Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".

high_performance_python

Code for the book "High Performance Python" by Micha Gorelick and Ian Ozsvald with OReilly

lime

Lime: Explaining the predictions of any machine learning classifier

natural-language-processing

Resources for "Natural Language Processing" Coursera course.

llama-recipes

Examples and recipes for Llama 2 model

lm-evaluation-harness

A framework for few-shot evaluation of autoregressive language models.

minGPT

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

nlpaug

Data augmentation for NLP

omnio

Python library for opening URIs as streaming file-like objects

optimum

🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools

Pretrained-Language-Model

Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

QNN

Tutorials on Quantized Neural Network using Tensorflow Lite

smoothquant

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

sparsegpt

Code for the paper "SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot".

sparseml

Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

USA-cities-and-states

Full list of US states and cities

vision

Datasets, Transforms and Models specific to Computer Vision