Quantile transform that is differentiable for PyTorch
Minimal PyTorch implementation of Point Transformer from "Point Transformer" by Zhao et al.
Code from "How useful is quantilization for mitigating specification-gaming?"
Explore training for quantized models
A collection of pandas & scikit-learn compatible transformers for preprocessing and feature engin...
파이썬과 케라스를 이용한 딥러닝/강화학습 주식투자 - 퀀트 투자, 알고리즘 트레이딩을 위한 최첨단 해법 입문 (개정판)
Torch-based tool for quantizing high-dimensional vectors using additive codebooks
tensor4 - pytorch to C++ convertor using lightweight templated tensor library
Implementation of Hourglass Transformer, in Pytorch, from Google and OpenAI
[ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
Implementation of RQ Transformer, proposed in the paper "Autoregressive Image Generation using Re...
Very usefull package to enable and provide custom transformers such as LogColumnTransformer, Bool...
Extends scikit-learn with new models, transformers, metrics, plotting.
Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch
You should use PySR to find scaling laws. Here's an example.
Implementation of the Point Transformer layer, in Pytorch