OhadRubin's repositories

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lightning-transformers

Flexible interface for high-performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra.

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al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

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Awesome-System-Design

This is a project submission for the course Advanced System Design in Tel Aviv University.

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client

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

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Colab-Hacks

Simple Hacks for Google Colaboratory to boost your productivity and help you to perform daily tasks.

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dalle-lightning

Refactoring dalle-pytorch and taming-transformers for TPU VM

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findimports

Static analysis of Python import statements

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FinRL

FinRL: The first open-source project for financial reinforcement learning. Please star. 🔥

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GC-DPR

Train Dense Passage Retriever (DPR) with a single GPU

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git-t5

Open source machine learning framework for training T5 models on source code in JAX/Flax.

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GooseSLURM

SLURM command line tools and scripts

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gradio

Create UIs for prototyping your machine learning model in 3 minutes

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haiku-mup

A port of muP to JAX/Haiku

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hydra

Hydra is a framework for elegantly configuring complex applications

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lightning-hydra-template

PyTorch Lightning + Hydra. A very user-friendly template for rapid and reproducible ML experimentation with best practices. ⚡🔥⚡

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Lightweighting_Cookbook

This project attempts to build neural network training and lightweighting cookbook including three kinds of lightweighting solutions, i.e., knowledge distillation, filter pruning, and quantization.

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pypeln

Concurrent data pipelines in Python >>>

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pyserini

Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations.

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python-package-template

A template repo for Python packages

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pytorch-lightning

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

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t-few

Code for T-Few from "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning"

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trl

Train transformer language models with reinforcement learning.

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