Search Results for "mac script executor"
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Showing 54 open source projects for "mac script executor"
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Tesseract.js
A pure Javascript Multilingual OCR
Tesseract.js is a pure Javascript port of the popular Tesseract OCR engine. Tesseract.js' library supports more than 100 languages, automatic text orientation and script detection, a simple interface for reading paragraph, word, and character bounding boxes. Tesseract.js can run either in a browser and on a server with NodeJS. Tesseract.js is a javascript library that gets words in almost any spoken language out of images. The main Tesseract.js functions (ex. recognize, detect) take an image... -
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Feishu ChatGPT
Voice dialogue, role-playing, multi-topic discussion, picture creation
... the efficient server-side hot update script you develop amaze the audience! Easily control Docker containerization technology and deploy code as you like! With some experience in payment function development, it really makes money fly! Understand some Linux scripting and socket programming. -
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Alpaca.cpp
Locally run an Instruction-Tuned Chat-Style LLM
... with a modified script and then quantized with llama.cpp the regular way. -
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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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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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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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gptee
LLMs done the UNIX-y way
Output from a language model using standard input as the prompt. Now supporting GPT3.5 chat completions! gptee was designed for use within shell scripts and other programs and also works in interactive shells. You can compose commands and execute them in a script. Proceed with caution before running arbitrary shell scripts. Using a chat completion model (like gpt-3.5-turbo), you can then inject a system message with -s or --system messages. For davinci and other non-chat models, the output... -
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FlubuCore
A cross platform build and deployment automation system
..., and IntelliSense make even the most complex script creation a breeze. Large number of often used built-in tasks like e.g. versioning, running tests, creating deployment packages, publishing NuGet packages, docker tasks, git tasts, sql tasks, npm tasks, executing PowerShell, managing IIS scripts and many more. -
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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... -
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OpenMLDB
OpenMLDB is an open-source machine learning database
... and inference. Real-time features are essential for many machine learning applications, such as real-time personalized recommendations and risk analytics. However, a feature engineering script developed by data scientists (Python scripts in most cases) cannot be directly deployed into production for online inference because it usually cannot meet the engineering requirements, such as low latency, high throughput and high availability. -
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SkyAGI
SkyAGI: Emerging human-behavior simulation capability in LLM
SkyAGI is a python package that demonstrates LLM's emerging capability in simulating believable human behaviors. Specifically, SkyAGI implements the idea of Generative Agents and delivers a role-playing game that creates a very interesting user experience. Different from previous AI-based NPC systems, SkyAGI's NPC generates very believable human responses. The interesting observations in this demo show a huge potential for rethinking game development in many aspects, such as NPC script writing. -
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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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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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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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pytorch-cpp
C++ Implementation of PyTorch Tutorials for Everyone
C++ Implementation of PyTorch Tutorials for Everyone. This repository provides tutorial code in C++ for deep learning researchers to learn PyTorch (i.e. Section 1 to 3) Interactive Tutorials are currently running on LibTorch Nightly Version. Libtorch only supports 64bit Windows and an x64 generator needs to be specified. Create all required script module files for pre-learned models/weights during the build. Requires installed python3 with PyTorch and torch-vision. You can choose to only build... -
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Laminar
Open-source all-in-one platform for engineering AI products
.... Tracing of text and image models is supported, audio models are coming soon. You can set up LLM-as-a-judge or Python script evaluators to run on each received span. Evaluators label spans, which is more scalable than human labeling, and especially helpful for smaller teams. Laminar lets you go beyond a single prompt. You can build and host complex chains, including mixtures of agents or self-reflecting LLM pipelines. -
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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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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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TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing models
... with a powerful Machine Learning tool set without reinventing the wheel. Since the APIs are kept as similar as possible you can immediately adapt any existing TensorFlow code in C# or F# with a zero learning curve. Take a look at a comparison picture and see how comfortably a TensorFlow/Python script translates into a C# program with TensorFlow.NET. -
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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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PerlPP
Perl preprocessor - embed Perl source in any file
Translates Text+Perl to Text. It can be used for any kind of text templating, e.g. code generation. No external modules are required, just a single file. Requires Perl 5.10.1+. PerlPP runs in two passes: it generates a Perl script from your input, and then it runs the generated script. If you see error at (eval ##) (for some number ##), it means there was an error in the generated script. The -D switch defines elements of %D. If you do not specify a value, the value true (a constant... -
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Coqui STT
The deep learning toolkit for speech-to-text
Coqui STT is a fast, open-source, multi-platform, deep-learning toolkit for training and deploying speech-to-text models. Coqui STT is battle-tested in both production and research. Multiple possible transcripts, each with an associated confidence score. Experience the immediacy of script-to-performance. With Coqui text-to-speech, production times go from months to minutes. With Coqui, the post is a pleasure. Effortlessly clone the voices of your talent and have the clone handle the problems... -
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Dickinson
Text generation language
Dickinson is a text-generation language. You can try out the language on the web without installing anything. Binaries for some platforms are available on the releases page. There is an install script that will try to download the right release for your computer. -
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Logic Programming and Deductive Database system (Tabled Prolog) for Unix, Mac, and Windows.