philjd Goto Github PK

accelerate

🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision

adamw_benchmark

Benchmark for optimizers with decoupled weight decay.

addons

Useful extra functionality for TensorFlow maintained by SIG-addons

contiguous_pytorch_params

Accelerate training by storing parameters in one contiguous chunk of memory.

detr

End-to-End Object Detection with Transformers

flashattention20triton

Annotated Triton implementation of Flash Attention2.0

fraiburg

Team frAIburg's code for the Audi Autonomous Driving Cup 2017

freiburg_groceries_dataset

Freiburg Groceries Dataset

generalize_spatial_relations

Code for the paper "Optimization Beyond the Convolution: Generalizing Spatial Relations with End-to-End Metric Learning" (ICRA 2018)

gps

Guided Policy Search

models

Models and examples built with TensorFlow

nanogpt

The simplest, fastest repository for training/finetuning medium-sized GPTs.

open-assistant

OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

philjd.github.io

https://philjd.github.io

pm_measurement

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch-lightning

The lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate

secr

Spatially Explicit Capture-Recapture

segmentation_models

Segmentation models with pretrained backbones. Keras.

squeeze_excitation

Experiments on squeeze and excitation networks for the bio-medical image analysis seminar.

tensorflow

Development fork.

test-tube

Python library to easily log, track machine learning code, experiments and parallelize hyperparameter search

tf-quaternion

An implementation of quaternions for and written in tensorflow. Fully differentiable.

thesis-template

A latex template for writing a Bachelor/Master thesis. (mirror of https://git.fachschaft.tf/fachschaft-public/thesis-template)

transformers

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