ThetaGang: an IBKR bot for collecting money

💬 Join the Matrix chat, we can get money together. Beat the capitalists at their own game with ThetaGang 📈 ThetaGang is an IBKR trading bot forcollecting premium by selling options using “The Wheel” strategy. The Wheelis a strategy that surfaced onReddit,but has been used by many in the past. This bot implements a slightlymodified version of The Wheel, with my own personal tweaks. I’ve been streaming most of the work on this project on Twitch, so follow meover there.

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SimCSE: Simple Contrastive Learning of Sentence Embeddings

SimCSE: Simple Contrastive Learning of Sentence Embeddings This repository contains the code and pre-trained models for our paper SimCSE: Simple Contrastive Learning of Sentence Embeddings. Overview We propose a simple contrastive learning framework that works with both unlabeled and labeled data. Unsupervised SimCSE simply takes an input sentence and predicts itself in a contrastive learning framework, with only standard dropout used as noise. Our supervised SimCSE incorporates annotated pairs from NLI datasets into contrastive learning by using entailment pairs as […]

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Code for Unsupervised Learning of Compositional Energy Concepts

This is the pytorch code for the paper Unsupervised Learning of Compositional Energy Concepts. Demo Please download a pretrained model at this link and then execute the following code to test a pretrained CelebA-HQ 128×128 COMET model python demo.py im_path=im0.png Please utilize the following command to run global factor decomposition on CelebA-HQ (or other datasets) python train.py –exp=celebahq –batch_size=12 –gpus=1 –cuda –train –dataset=celebahq –step_lr=500.0 You may further run the code on high-resolution 128×128 images below python train.py –exp=celebahq_128    

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Stochastic Scene-Aware Motion Prediction

Stochastic Scene-Aware Motion Prediction [Project Page][Paper] Description This repository contains the training code for MotionNet and GoalNet of SAMP. Installation To install the necessary dependencies run the following command: pip install -r requirements.txt The code has been tested with Python 3.8.10, CUDA 10.0, CuDNN 7.5 and PyTorch 1.7.1 on Ubuntu 20.04. Training Data The training data for MotionNet and GoalNet could be found in the website downloads. Or could be extractedfrom the Unity runtime code. Update    

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Automatically remove user join messages when the user leaves the server

Automatically remove user join messages when the user leaves the server. Installation You will need to install poetry to run this bot locally for levelopment, but running in docker is preferred for production deployment. Poetry can be installed using the following command: Windows: py -3 -m pip install poetry. Linux/Mac: python3 -m pip install poetry. To install the dependencies you can then run poetry install in the folder you cloned the repository to. You need to copy .env.example to .env […]

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Compare neural networks by their feature similarity

A tiny package to compare two neural networks in PyTorch. There are many ways to compare two neural networks, but one robust and scalable way is using the Centered Kernel Alignment (CKA) metric, where the features of the networks are compared. Centered Kernel Alignment Centered Kernel Alignment (CKA) is a representation similarity metric that is widely used for understanding the representations learned by neural networks. Specifically, CKA takes two feature maps / representations X and Y as input and computes […]

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Custom Implementation of Non-Deep Networks

Custom Implementation of Non-deep Networks arXiv:2110.07641 Ankit Goyal, Alexey Bochkovskiy, Jia Deng, Vladlen Koltun Official Repository https://github.com/imankgoyal/NonDeepNetworks Overview: Depth is the hallmark of DNNs. But more depth means more sequential computation and higher latency. This begs the question — is it possible to build high-performing “non-deep” neural networks? We show that it is. We show, for the first time, that a network with a depth of just 12 can achieve top-1 accuracy over 80% on ImageNet, 96% on CIFAR10, and […]

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Simple Pixelbot for Diablo 2 Resurrected written in python and opencv

Simple Pixelbot for Diablo 2 Resurrected written in python and opencv. Obviously only use it in offline mode as it is against the TOS of Blizzard to use it in online mode! Join the Discord Channel for help and discussions. Supported features Run Pindle, Eldtritch, Shenk Pickit with per item config. Stash picked up items (using all 4 stashes) Prebuff Revive Merc if dead Heal at Malah if needed Take potions and chicken if in trouble during fights Check for […]

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