Deep Learning, NLP, NMT, AI, ML
$ sh build.sh $ sh start.sh $ sh build_dev.sh $ sh bind_dev.sh $ sh start_dev.sh Create Todo curl –location –request POST ‘http://127.0.0.1:3000/todo’ –header ‘Content-Type: application/json’ –data-raw ‘{ “id”: null, “title”: “{description}”, “description”: “{description}” }’ Get all Todos curl –location –request GET ‘http://127.0.0.1:3000/todo’ Get Todo by Id
Read moreRenders possibly malicious PDF files and outputs harmless PDF files To do this, the PDF files are rendered and converted to images using PyMuPDF.The images are then saved to a new PDF file using img2pdf. This ensures no visual data is lost,but any scripts/external references/flash files are removed. Instalation: git clone https://github.com/lacioffi/PDFSanitizer cd PDFSanitizer pip install -r requirements.txt Usage:
Read moreduolingo account creator that uses your invite code to get you free duolingo plus Step 1: Get your invite code Go to your duolingo profile page and click on “Invite friends” Copy the url Now, paste your url into a text editor, and copy the code Step 2: Get free duolingo plus You need python to run this code Clone the repository Run pip install -r requirements.txt in the directory that this code is located After that, put proxies in […]
Read moreIoana Bica, Daniel Jarrett, Mihaela van der Schaar Neural Information Processing Systems (NeurIPS) 2021 Dependencies The code was implemented in Python 3.6 and the following packages are needed for running it: gym==0.17.2 numpy==1.18.2 pandas==1.0.4 tensorflow==1.15.0 torch==1.6.0 tqdm==4.32.1 scipy==1.1.0 scikit-learn==0.22.2 stable-baselines==2.10.1 Running and evaluating the model: The control tasks used for experiments are from OpenAI gym [1]. Each control task is associated with a true rewardfunction (unknown to the imitation algorithm). In each case, the “expert” demonstrator can be obtained by […]
Read moreBem vindo ao jogo Mastermind! O jogo consiste em adivinhar uma senha que será gerada a cada partida, composta por quatro cores dentre as citadas: amarelo, verde, azul, roxo, vermelho, laranja.Inicialmente será necessário inserir quantas tentativas você deseja ter para acertar a senha (a recomendação é 10).Existem 10 pinos de cada cor no total para serem usados, não podendo exceder esse número por pino na partida.A cada tentativa será informado por pinos brancos se a cor está na posição certa, […]
Read moreThis repository is a modification of: https://github.com/openai/gpt-2 for our specific purposes The objective of this API is to provide the 3 best possible responses to sentences that the user would input via http GET request as a parameter. This API that can help developers use GPT2 for their web application projects without the hassle of figuring out how GPT2 works. This API was used in a dating app project, where given the sentences the users exchanged the API had to […]
Read moreThis is a PyTorch implementation of the MD-GNN, and the code includes the following modules: Datasets (Cora, Citeseer, Pubmed, Synthetic, and ZINC) Training paradigm for node classification, graph classification, and graph regression tasks Visualization Evaluation metrics Main Requirements dgl==0.4.3.post2 networkx==2.4 numpy==1.18.1 ogb==1.1.1 scikit-learn==0.22.2.post1 scipy==1.4.1 torch==1.5.0 Description train.py main() — Train a new model for node classification task on the Cora, Citeseer, and Pubmed datasets evaluate() — Test the learned model for node classification task on the Cora, Citeseer, and Pubmed […]
Read more
This script utilises payload dumper and image extractor tools to extract the apps from the system.img of an android OTA file. It works on Windows OS. Requirements: Windows 10 Python3 installed and added to environment variable pip3 installed and added to environment variable Python Modules -> protobuf==3.6.0, six==1.11.0, bsdiff4>=1.1.5 If you face issues, install Windows 10 SDK & C++ build tools. Download the build tools here. Launch the Visual Studio Installer and select the Desktop development with C++ option. Install […]
Read more
It is a simple library to speed up CLIP inference up to 3x (K80 GPU) Usage Install clip-onnx module and requirements first. Use this trick !pip install git+https://github.com/Lednik7/CLIP-ONNX.git Example in 3 steps Download CLIP image from repo !wget -c -O CLIP.png https://github.com/openai/CLIP/blob/main/CLIP.png?raw=true Load standard CLIP model, image, text on cpu
Read more