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