Search Results for "interact"
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Showing 20 open source projects for "interact"
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shimmy
Python-free Rust inference server
...Written primarily in Rust, the tool provides a small standalone binary that exposes an API compatible with the OpenAI interface, allowing existing applications to interact with local models without significant code changes. This compatibility enables developers to replace remote AI services with locally hosted models while keeping their existing software architecture intact. Shimmy focuses on performance and simplicity, using efficient runtime components to minimize memory usage and startup time compared to heavier inference frameworks. ... -
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TFX
TFX is an end-to-end platform for deploying production ML pipelines
...TFX pipelines can be orchestrated using Apache Airflow and Kubeflow Pipelines. Both the components themselves and the integrations with orchestration systems can be extended. TFX components interact with an ML Metadata backend that keeps a record of component runs, input and output artifacts, and runtime configuration. This metadata backend enables advanced functionality like experiment tracking or warm starting/resuming ML models from previous runs. -
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UnrealCV
Connecting Computer Vision to Unreal Engine
UnrealCV is a project to help computer vision researchers build virtual worlds using Unreal Engine (UE). It extends UE with a plugin. UnrealCV can be used in two ways. The first one is using a compiled game binary with UnrealCV embedded. This is as simple as running a game, no knowledge of Unreal Engine is required. The second is installing the UnrealCV plugin into Unreal Engine and using the editor to build a new virtual world. -
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huggingface_hub
The official Python client for the Huggingface Hub
The huggingface_hub library allows you to interact with the Hugging Face Hub, a platform democratizing open-source Machine Learning for creators and collaborators. Discover pre-trained models and datasets for your projects or play with the thousands of machine-learning apps hosted on the Hub. You can also create and share your own models, datasets, and demos with the community. -
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5
Gradio
Create UIs for your machine learning model in Python in 3 minutes
...Gradio can be embedded in Python notebooks or presented as a webpage. A Gradio interface can automatically generate a public link you can share with colleagues that lets them interact with the model on your computer remotely from their own devices. Once you've created an interface, you can permanently host it on Hugging Face. Hugging Face Spaces will host the interface on its servers and provide you with a link you can share. One of the best ways to share your machine learning model, API, or data science workflow with others is to create an interactive demo that allows your users or colleagues to try out the demo in their browsers. -
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RL with PyTorch
Clean, Robust, and Unified PyTorch implementation
...The repository is structured so that users can easily experiment with different algorithms and training environments. Many examples demonstrate how agents learn to interact with simulated environments through trial and error using reinforcement learning principles. The codebase emphasizes clarity and modular design so that researchers can extend the implementations or use them for experimentation and benchmarking. -
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seq2seq-couplet
Play couplet with seq2seq model
...The repository includes the code needed to train the model, configure file paths and hyperparameters, and evaluate progress through loss and BLEU score tracking. It also supports serving the trained model through a web service, allowing users to interact with the system after training is complete. In addition to local execution, the project includes Docker files, which make it easier to package and deploy the application in a more reproducible way. The repository also points users to an external dataset source and documents vocabulary formatting requirements for custom datasets, showing that it is meant for both experimentation and extension. -
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Computer vision projects
computer vision projects | Fun AI projects related to computer vision
...The repository includes multiple demonstration systems implemented using languages such as Python and C++, covering topics ranging from object detection to embedded vision systems. Many of the projects illustrate how computer vision algorithms can interact with hardware platforms, including robotics systems and edge computing devices. The repository provides examples that combine machine learning models with real-world applications such as robotic arms, video analysis, and automated visual measurement systems. -
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picoGPT
An unnecessarily tiny implementation of GPT-2 in NumPy
...Because the code is intentionally lightweight, it is often used as a teaching resource for students learning about natural language processing and deep learning architectures. Developers can explore the repository to understand how language models generate text and how transformer components interact within the architecture. -
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10
AirSim
A simulator for drones, cars and more, built on Unreal Engine
AirSim is an open-source, cross platform simulator for drones, cars and more vehicles, built on Unreal Engine with an experimental Unity release in the works. It supports software-in-the-loop simulation with popular flight controllers such as PX4 & ArduPilot and hardware-in-loop with PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. AirSim's development is oriented towards the goal of creating a... -
11
PySC2
StarCraft II learning environment
...This is a collaboration between DeepMind and Blizzard to develop StarCraft II into a rich environment for RL research. PySC2 provides an interface for RL agents to interact with StarCraft 2, getting observations and sending actions. The easiest way to get PySC2 is to use pip. That will install the pysc2 package along with all the required dependencies. virtualenv can help manage your dependencies. You may also need to upgrade pip: pip install --upgrade pip for the pysc2 install to work. If you're running on an older system you may need to install libsdl libraries for the pygame dependency. -
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Talking Head Anime from a Single Image
Demo for the "Talking Head Anime from a Single Image"
...This allows the software to create realistic animated frames while preserving the identity and appearance of the original character. The repository includes demo applications that allow users to interact with the system through graphical controls or webcam input to drive character motion. These demonstrations illustrate how generative neural rendering can be used to build real-time avatar systems for virtual characters. -
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Machine Learning From Scratch
Bare bones NumPy implementations of machine learning models
...Because the code avoids external machine learning libraries, it exposes the full logic behind model training, optimization, and prediction processes. The project also provides examples and explanations that illustrate how the algorithms behave and how different components interact during training. -
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nGraph
nGraph has moved to OpenVINO
...We strongly believe in providing freedom, performance, and ease of use to AI developers. Our documentation has extensive information about how to use nGraph Compiler stack to create an nGraph computational graph, integrate custom frameworks, and to interact with supported backends. -
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Spotlight
Deep recommender models using PyTorch
...For example, generate_sequential generates a Markov-chain-derived interaction dataset, where the next item a user chooses is a function of their previous interactions. Recommendations can be seen as a sequence prediction task: given the items a user has interacted with in the past, what will be the next item they will interact with? Spotlight provides a range of models. -
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MIT Deep Learning
Tutorials, assignments, and competitions for MIT Deep Learning
...Many of the tutorials include practical implementations that demonstrate tasks such as image classification, generative models, and neural network training workflows. The materials are structured as Jupyter notebooks so that learners can interact with the code and experiment with models while studying the concepts. The repository is designed to complement academic coursework and often evolves as new course material is developed. Because the tutorials are designed for educational use, they emphasize clear explanations and step-by-step demonstrations of deep learning concepts. -
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TorchCraft
Connecting Torch to StarCraft
...This white paper argues for using RTS games as a benchmark for AI research, and describes the design and components of TorchCraft. TorchCraft is a BWAPI module that sends StarCraft data out over a ZMQ connection. This lets you parse StarCraft data and interact with BWAPI from anywhere. The TorchCraft client should be installed from C++, Python, or Lua. We provide off-the-shelf solutions for Python and Lua. -
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AWS IoT Arduino Yún SDK
SDK for connecting to AWS IoT from an Arduino Yún
...The AWS-IoT-Arduino-Yún-SDK provides APIs to let users publish messages to AWS IoT and subscribe to MQTT topics to receive messages transmitted by other devices or coming from the broker. This allows to interact with the standard MQTT PubSub functionality of AWS IoT. -
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The Star Ships Learning Framework (SSLF) provides basic routines and methods in order to interact with the space shooter Star Ships V2.1. It provides the necessary interfaces for controlling the program's ships and its logic from outside the game.
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20
bnns
Research tool for interactive training of artificial neural networks.
BNNS is a research tool for interactive training of artificial neural networks based on the Response Function Plots visualization method. It enables users to simulate, visualize and interact in the learning process of a Multi-Layer Perceptron on tasks which have a 2D character. Tasks like the famous two-spirals task or classification of satellite image data.
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