Search Results for "input-output model"
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Showing 434 open source projects for "input-output model"
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MATLAB Deep Learning Model Hub
Discover pretrained models for deep learning in MATLAB
Discover pre-trained models for deep learning in MATLAB. Pretrained image classification networks have already learned to extract powerful and informative features from natural images. Use them as a starting point to learn a new task using transfer learning. Inputs are RGB images, the output is the predicted label and score. -
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Real-ESRGAN GUI
Cross-platform GUI for image upscaler Real-ESRGAN
... arm64single-architecture applications by themselves. Real-ESRGAN can only enlarge the input image with a fixed 2-4x magnification (related to the selected model). This functionality is achieved by downsampling using a conventional scaling algorithm after multiple calls to Real-ESRGAN. Split each frame of the GIF and record the duration, zoom in one by one and then merge. Drag an image file or directory to any position in the window, and its path can be automatically set as the input. -
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JupyterLab
JupyterLab computational environment
... new workflows for interactive computing. JupyterLab also offers a unified model for viewing and handling data formats. JupyterLab understands many file formats (images, CSV, JSON, Markdown, PDF, Vega, Vega-Lite, etc.) and can also display rich kernel output in these formats. See File and Output Formats for more information. To navigate the user interface, JupyterLab offers customizable keyboard shortcuts and the ability to use key maps from vim, emacs, and Sublime Text in the text editor. -
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CadQuery
A python parametric CAD scripting framework based on OCCT
CadQuery is an intuitive, easy-to-use Python library for building parametric 3D CAD models. It has several goals. Build models with scripts that are as close as possible to how you’d describe the object to a human, using a standard, already established programming language. Create parametric models that can be very easily customized by end users. Output high-quality CAD formats like STEP and AMF in addition to traditional STL. Provide a non-proprietary, plain text model format that can... -
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Text Generation Web UI
A gradio web UI for running Large Language Models like LLaMA
... efficient text streaming. Parameter presets, 8-bit mode. Layers splitting across GPU(s), CPU, and disk. CPU mode, FlexGen, DeepSpeed ZeRO-3, API with streaming and without streaming. LLaMA model, including 4-bit GPTQ. RWKV model, LoRA (loading and training), Softprompts, and extensions. -
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MCPTools
A command-line interface for interacting with MCP
mcptools is a command-line interface designed for interacting with Model Context Protocol (MCP) servers using both standard input/output and HTTP transport methods. It allows users to discover and call tools, list resources, and interact with MCP-compatible servers. The tool supports various output formats and includes features like an interactive shell, project scaffolding, and server alias management. -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
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AIMET
AIMET is a library that provides advanced quantization and compression
Qualcomm Innovation Center (QuIC) is at the forefront of enabling low-power inference at the edge through its pioneering model-efficiency research. QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware... -
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LightGBM
Gradient boosting framework based on decision tree algorithms
LightGBM or Light Gradient Boosting Machine is a high-performance, open source gradient boosting framework based on decision tree algorithms. Compared to other boosting frameworks, LightGBM offers several advantages in terms of speed, efficiency and accuracy. Parallel experiments have shown that LightGBM can attain linear speed-up through multiple machines for training in specific settings, all while consuming less memory. LightGBM supports parallel and GPU learning, and can handle... -
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UI-TARS Desktop
A GUI Agent app based on UI-TARS to control your computer using AI
UI-TARS Desktop is a graphical user interface (GUI) agent application that leverages the UI-TARS vision-language model to enable natural language control of computers. This cross-platform tool supports both Windows and macOS, allowing users to perform tasks through intuitive commands. Key features include screenshot-based visual recognition, precise mouse and keyboard control, and real-time feedback on actions. The application facilitates seamless interaction with the computer, enhancing user... -
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MediaPipe
Cross-platform, customizable ML solutions for live and streaming media
MediaPipe offers open-source cross-platform, customizable ML solutions for live and streaming media. Provides segmentation masks for prominent humans in the scene. MediaPipe Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices. It employs machine learning (ML) to infer the 3D surface geometry, requiring only a single camera input without the need for a dedicated depth sensor. Utilizing lightweight model architectures together with GPU... -
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Bytewax
Python Stream Processing
... processing engine that uses a dataflow computational model to provide parallelizable stream processing and event processing capabilities similar to Flink, Spark, and Kafka Streams. You can use Bytewax for a variety of workloads from moving data à la Kafka Connect style all the way to advanced online machine learning workloads. Bytewax is not limited to streaming applications but excels anywhere that data can be distributed at the input and output. -
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SageMaker TensorFlow Training Toolkit
Toolkit for running TensorFlow training scripts on SageMaker
... to a model.tar.gz file in S3 containing serialized model data, and a Docker image used to serve predictions with that model. A Batch Transform job runs an offline-inference job using your TensorFlow Serving model. Input data in S3 is converted to HTTP requests, and responses are saved to an output bucket in S3. -
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AIaC
Artificial Intelligence Infrastructure-as-Code Generator
aiac is a command line tool to generate IaC (Infrastructure as Code) templates, configurations, utilities, queries and more via OpenAI's API. The CLI allows you to ask the model to generate templates for different scenarios (e.g. "get terraform for AWS EC2"). It will make the request, and store the resulting code to a file, or simply print it to standard output. By default, aiac uses the same model used by ChatGPT, but allows using different models. -
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kpt
Automate Kubernetes Configuration Editing
kpt is a package-centric toolchain that enables a WYSIWYG configuration authoring, automation, and delivery experience, which simplifies managing Kubernetes platforms and KRM-driven infrastructure (e.g., Config Connector, Crossplane) at scale by manipulating declarative Configuration as Data. Any general-purpose or domain-specific language can be used to create functions to transform and/or validate the YAML KRM input/output format, but we provide SDKs to simplify the function authoring process... -
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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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Prompt Declaration Language
Prompt Declaration Language is a declarative prompt programming lang
LLMs will continue to change the way we build software systems. They are not only useful as coding assistants, providing snipets of code, explanations, and code transformations, but they can also help replace components that could only previously be achieved with rule-based systems. Whether LLMs are used as coding assistants or software components, reliability remains an important concern. LLMs have a textual interface and the structure of useful prompts is not captured formally. Programming... -
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JSBSim
An open source flight dynamics & control software library
JSBSim is a multi-platform, general purpose object-oriented Flight Dynamics Model (FDM) written in C++. The FDM is essentially the physics & math model that defines the movement of an aircraft, rocket, etc., under the forces and moments applied to it using the various control mechanisms and from the forces of nature. JSBSim can be run in a standalone batch mode flight simulator (no graphical displays a.k.a. console mode) for testing and study, or integrated with the Unreal engine, FlightGear... -
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iTerm MCP
A Model Context Protocol server that executes commands
A Model Context Protocol server that executes commands in the current iTerm session, providing AI assistants with the ability to interact with REPL environments and command-line interfaces. -
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pyglet
pyglet is a cross-platform windowing and multimedia library for Python
Pyglet is a cross-platform windowing and multimedia library for Python, intended for developing games and other visually rich applications. It supports windowing, input event handling, OpenGL graphics, loading images and videos, and playing sounds and music. -
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Deepchecks
Test Suites for validating ML models & data
... your model and evaluate it. To run a specific single check, all you need to do is import it and then to run it with the required (check-dependent) input parameters. More details about the existing checks and the parameters they can receive can be found in our API Reference. An ordered collection of checks, that can have conditions added to them. The Suite enables displaying a concluding report for all of the Checks that ran. -
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Lapis
A web framework for Lua and OpenResty written in MoonScript
Lapis is a framework for building web applications in Lua (or MoonScript) that primarily targets OpenResty, a high-performance web platform that runs on a customized version of Nginx. Lapis can also be used in other server environments, being compatible with any modern version of Lua. With OpenResty, Lua is run directly inside of the Nginx worker using LuaJIT, giving you the smallest barrier between the webserver and your code. Have a look at Web Framework Benchmarks just to see how... -
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Nightingale OS
A small operating system where I experiment and learn osdev
... language with a strong safety model. -
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Open Asset Import Library
The open-asset-importer-library repository
... for use in game engines / realtime rendering systems of any kind, but it is not limited to this purpose. In the past, it has been used in a wide range of applications. Written in C++, it is available under a liberal BSD license. There is a C API as well as bindings to various other languages, including C#, Python and D. Assimp loads all input model formats into one straightforward data structure for further processing. -
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Moshi
A speech-text foundation model for real time dialogue
Moshi is a speech-text foundation model and full-duplex spoken dialogue framework. It uses Mimi, a state-of-the-art streaming neural audio codec. Mimi processes 24 kHz audio, down to a 12.5 Hz representation with a bandwidth of 1.1 kbps, in a fully streaming manner (latency of 80ms, the frame size), yet performs better than existing, non-streaming, codecs like SpeechTokenizer (50 Hz, 4kbps), or SemantiCodec (50 Hz, 1.3kbps). Moshi models two streams of audio: one corresponds to Moshi...
