Search Results for "notepad++ python script"
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Showing 38 open source projects for "notepad++ python script"
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marimo
A reactive notebook for Python
marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots... -
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Chatterbox
SoTA open-source TTS
Chatterbox is Resemble AI's first production-grade open source TTS model. Licensed under MIT, Chatterbox has been benchmarked against leading closed-source systems like ElevenLabs and is consistently preferred in side-by-side evaluations. Whether you're working on memes, videos, games, or AI agents, Chatterbox brings your content to life. It's also the first open source TTS model to support emotion exaggeration control, a powerful feature that makes your voices stand out. Try it now on our... -
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MoneyPrinterTurbo
Generate short videos with one click using AI LLM
MoneyPrinterTurbo is an AI-driven tool that enables users to generate high-definition short videos with minimal input. By providing a topic or keyword, the system automatically creates video scripts, sources relevant media assets, adds subtitles, and incorporates background music, resulting in a polished video ready for distribution. -
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firerpa LAMDA
The most powerful Android RPA agent framework
lamda is an Android RPA agent framework that provides visual remote desktop control and automation at scale, geared toward testing, automation validation, and device management. It exposes a clean UI to monitor and interact with connected devices and includes tooling to script actions reliably across apps and OS versions. The project emphasizes low-friction setup and powerful control primitives so teams can move from interactive validation to repeatable automation. A public wiki, releases... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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GPT-2
Code for the paper Language Models are Unsupervised Multitask Learners
This repository contains the code and model weights for GPT-2, a large-scale unsupervised language model described in the OpenAI paper “Language Models are Unsupervised Multitask Learners.” The intent is to provide a starting point for researchers and engineers to experiment with GPT-2: generate text, fine‐tune on custom datasets, explore model behavior, or study its internal phenomena. The repository includes scripts for sampling, training, downloading pre-trained models, and utilities for... -
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Quark Agent
Quark Agent - Your AI-powered Android APK Analyst
With Quark Agent, you can perform analyses using only natural language. It creates Quark Script code following your ideas and adjusts the code promptly as you provide feedback. -
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Elyra
Elyra extends JupyterLab with an AI centric approach
Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page. -
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Hamilton DAGWorks
Helps scientists define testable, modular, self-documenting dataflow
Hamilton is a lightweight Python library for directed acyclic graphs (DAGs) of data transformations. Your DAG is portable; it runs anywhere Python runs, whether it's a script, notebook, Airflow pipeline, FastAPI server, etc. Your DAG is expressive; Hamilton has extensive features to define and modify the execution of a DAG (e.g., data validation, experiment tracking, remote execution). To create a DAG, write regular Python functions that specify their dependencies with their parameters... -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime... -
The All-in-One Commerce Platform for Businesses - ShopifyShopify is a leading all-in-one commerce platform that enables businesses to start, build, and grow their online and physical stores. It offers tools to create customized websites, manage inventory, process payments, and sell across multiple channels including online, in-person, wholesale, and global markets. The platform includes integrated marketing tools, analytics, and customer engagement features to help merchants reach and retain customers. Shopify supports thousands of third-party apps and offers developer-friendly APIs for custom solutions. With world-class checkout technology, Shopify powers over 150 million high-intent shoppers worldwide. Its reliable, scalable infrastructure ensures fast performance and seamless operations at any business size.
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BudouX
Standalone, small, language-neutral
Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning-powered line break organizer tool. It is standalone. It works with no dependency on third-party word segmenters such as Google cloud natural language API. It is small. It takes only around 15 KB including its machine learning model. It's reasonable to use it even on the client-side. It is language-neutral. You can train a model for any language by feeding a dataset to BudouX’s training script. -
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nanochat
The best ChatGPT that $100 can buy
...: you can boot a fresh GPU box and drive the whole pipeline via a single script, producing a usable chat model in hours and a clear markdown report of what happened. The code is written to be read—concise training loops, transparent configs, and minimal wrappers—so you can audit each step, tweak it, and rerun without getting lost in framework indirection. -
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Gemini Fullstack LangGraph Quickstart
Get started w/ building Fullstack Agents using Gemini 2.5 & LangGraph
... Search API, and performs reflective reasoning to identify knowledge gaps. It then iteratively refines its search until it produces a comprehensive, well-cited answer synthesized by the Gemini model. The repository provides both a browser-based chat interface and a command-line script (cli_research.py) for executing research queries directly. For production deployment, the backend integrates with Redis and PostgreSQL to manage persistent memory, streaming outputs, & background task coordination. -
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Weights and Biases
Tool for visualizing and tracking your machine learning experiments
..., hyperparameters, launch commands, input data, and resulting model weights. Set wandb.config once at the beginning of your script to save your hyperparameters, input settings (like dataset name or model type), and any other independent variables for your experiments. This is useful for analyzing your experiments and reproducing your work in the future. Setting configs also allows you to visualize the relationships between features of your model architecture or data pipeline and model performance. -
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Asteroid
The PyTorch-based audio source separation toolkit for researchers
... in a flexible way to create new systems. Extending the toolkit with new features is simple. Add a new filterbank, separator architecture, dataset or even recipe very easily. Recipes provide an easy way to reproduce results with data preparation, system design, training and evaluation in a single script. This is an essential tool for the community! The default logger is TensorBoard in all the recipes. From the recipe folder, you can run the following to visualize the logs of all your runs. -
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Horovod
Distributed training framework for TensorFlow, Keras, PyTorch, etc.
Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data... -
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Amiga Memories
A walk along memory lane
Amiga Memories is a project (started & released in 2013) that aims to make video programmes that can be published on the internet. The images and sound produced by Amiga Memories are 100% automatically generated. The generator itself is implemented in Squirrel, the 3D rendering is done on GameStart 3D. An Amiga Memories video is mostly based on a narrative. The purpose of the script is to define the spoken and written content. The spoken text will be read by a voice synthesizer (Text To Speech... -
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ImPromptu
Domain Agnostic Prompts for Savvy Professionals
... today then head over to the prompt generator and let the magic happen. This script will literally write your prompts for you, as if chatGPT wasn't enough magic for you already. -
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G-Diffuser Bot
Discord bot and Interface for Stable Diffusion
The first release of the all-in-one installer version of G-Diffuser is here. This release no longer requires the installation of WSL or Docker and has a systray icon to keep track of and launch G-Diffuser components. The infinite zoom scripts have been updated with some improvements, notably a new compositer script that is hundreds of times faster than before. The first release of the all-in-one installer is here. It notably features much easier "one-click" installation and updating, as well... -
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BCI
BCI: Breast Cancer Immunohistochemical Image Generation
Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix. We have released the trained model on BCI and LLVIP datasets. We host a competition for breast cancer immunohistochemistry image generation on Grand Challenge. Project pix2pix provides a python script to generate pix2pix training data in the form of pairs of images {A,B}, where A and B are two different depictions of the same underlying scene, these can be pairs {HE, IHC}. Then we can learn to translate A(HE images... -
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Video Pre-Training
Learning to Act by Watching Unlabeled Online Videos
.... for building houses or early-game tasks), and inference scripts that instantiate agents from pretrained weights. Key modules include the behavioral cloning logic, the agent wrapper, and data loading pipelines (with an accessible skeleton for loading Minecraft demonstration data). The repo also includes a run_agent.py script for testing an agent interactively, and an agent.py module encapsulating the control logic. -
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TensorFlow Backend for ONNX
Tensorflow Backend for ONNX
Open Neural Network Exchange (ONNX) is an open standard format for representing machine learning models. ONNX is supported by a community of partners who have implemented it in many frameworks and tools. TensorFlow Backend for ONNX makes it possible to use ONNX models as input for TensorFlow. The ONNX model is first converted to a TensorFlow model and then delegated for execution on TensorFlow to produce the output. This is one of the two TensorFlow converter projects which serve different... -
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GANformer
Generative Adversarial Transformers
This is an implementation of the GANformer model, a novel and efficient type of transformer, explored for the task of image generation. The network employs a bipartite structure that enables long-range interactions across the image, while maintaining computation of linearly efficiency, that can readily scale to high-resolution synthesis. The model iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of... -
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CCTV Frame Timestamp Extractor
CCTV Footage Timestamp Search Tool
Python script to address the problem of manually locating required event timestamps from carved CCTV DVR footages. Full details can be found in the paper published in Eighteenth Annual IFIP WG 11.9 International Conference on Digital Forensics. Link to paper: https://link.springer.com/chapter/10.1007/978-3-031-10078-9_8 The project has been divided into four modules: Framextract.py- Extracts frames from video footages Reconstruct.py- Attempts to repair unplayable video by extracting... -
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GPT Neo
An implementation of model parallel GPT-2 and GPT-3-style models
An implementation of model & data parallel GPT3-like models using the mesh-tensorflow library. If you're just here to play with our pre-trained models, we strongly recommend you try out the HuggingFace Transformer integration. Training and inference is officially supported on TPU and should work on GPU as well. This repository will be (mostly) archived as we move focus to our GPU-specific repo, GPT-NeoX. NB, while neo can technically run a training step at 200B+ parameters, it is very... -
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Age and Gender Estimation
Keras implementation of a CNN network for age and gender estimation
Keras implementation of a CNN network for age and gender estimation. This is a Keras implementation of a CNN for estimating age and gender from a face image [1, 2]. In training, the IMDB-WIKI dataset is used. Because the face images in the UTKFace dataset is tightly cropped (there is no margin around the face region), faces should also be cropped in demo.py if weights trained by the UTKFace dataset is used. Please set the margin argument to 0 for tight cropping. You can evaluate a trained...
