Search Results for "run sackboy run" - Page 3
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Showing 1310 open source projects for "run sackboy run"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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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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Jupyter Docker Stacks
Ready-to-run Docker images containing Jupyter applications
Jupyter Docker Stacks provides a curated set of ready-to-run Docker container images that bundle Jupyter applications with popular data science and computing tools, enabling users to quickly start working in a reproducible environment. These stacks support a range of use cases, from lightweight base notebook images to full featured environments that include scientific computing libraries, machine learning tools, and IDE-like notebook interfaces, all within Docker containers that run consistently across machines. ... -
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RamaLama
Simplifies the local serving of AI models from any source
...It abstracts away much of the complexity of configuring AI runtimes, dependencies, and hardware optimizations by detecting available GPUs (or falling back to CPU) and automatically pulling a container image pre-configured for the detected hardware environment. Developers can use familiar container commands to pull, run, and interact with AI models from any source, treating models similarly to how container images are handled in OCI workflows. RamaLama supports multiple model registries and offers a REST API or chatbot interface for interacting with running models, making it flexible for local development, testing, or integration into larger systems. -
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Promgen
Promgen is a configuration file generator for Prometheus
Promgen is a configuration file generator for Prometheus. Promgen is a web application written with Django and can help you do several jobs. The primary management UI is a Django application and many of the concepts that apply to a typical Django application will apply to Promgen. Configure Prometheus to load the target file from Prometheus and configure AlertManager to send notifications back to Promgen. Arbitrary Django settings can be set for the Promgen web app by adding those under the... -
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AWS Neuron
Powering Amazon custom machine learning chips
AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. ... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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TensorRT Node for ComfyUI
Enables the best performance on NVIDIA RTX Graphics Cards
ComfyUI_TensorRT is an extension that lets ComfyUI run AI inference through NVIDIA’s TensorRT, aiming to get faster, more efficient execution on supported GPUs. It bridges the gap between ComfyUI’s flexible, node-based workflows and TensorRT’s highly optimized engine format. The result is that complex diffusion or image-processing graphs can be accelerated without the user having to rewrite the pipeline. -
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django-braces
Reusable, generic mixins for Django
django-braces provides useful Mixins for Django's class-based views. Most of these mixins replicate the behavior of Django's function-based view decorators. Others solve common headaches with working with class-based views. django-braces is stable and time-tested. It does not receive a lot of updates and is not in active development. django-braces also only officially supports Python versions that are still receiving fixes and Django LTS versions. django-braces will work with a most modern... -
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PyBoy
Game Boy emulator written in Python
PyBoy is an open-source Game Boy emulator written in Python, designed for both gameplay and AI experimentation. It allows users to run classic Game Boy games while providing a powerful API for automation, scripting, and reinforcement learning. Developers can interact directly with game memory, inputs, and screen data, making it ideal for training bots and analyzing game mechanics. PyBoy emphasizes performance, enabling accelerated emulation speeds and frame skipping for large-scale simulations. ... -
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AutoGPT
Powerful tool that lets you create and run intelligent agents
AutoGPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set. As one of the first examples of GPT-4 running fully autonomously, AutoGPT pushes the boundaries of what is possible with AI. -
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Clarity AI Upscaler
AI Image Upscaler & Enhancer
...Unlike traditional interpolation-based upscaling algorithms, the system generates additional visual information that improves perceived clarity and sharpness. The project is intended as a free and open alternative to commercial AI upscaling tools, allowing developers and digital artists to run the technology locally or integrate it into their own workflows. The repository includes a full application environment with scripts, configuration files, and model support that allow users to run the upscaler as a standalone tool or integrate it into other pipelines. -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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FlexLLMGen
Running large language models on a single GPU
FlexLLMGen is an open-source inference engine designed to run large language models efficiently on limited hardware resources such as a single GPU. The system focuses on high-throughput generation workloads where large batches of text must be processed quickly, such as large-scale data extraction or document analysis tasks. Instead of requiring expensive multi-GPU systems, the framework uses techniques such as memory offloading, compression, and optimized batching to run large models on commodity hardware. ... -
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StreamCap
Multi-Platform Live Stream Automatic Recording Tool
...It offers a wide range of output formats and includes automatic transcoding features to standardize recordings after capture. StreamCap also integrates notification systems to alert users when streams begin, enhancing real-time responsiveness. Designed for flexibility, it can run on desktop or web environments, making it suitable for both casual archiving and professional content workflows. -
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Synapse
Matrix reference homeserver
...Rooms can be located using convenience aliases like #matrix:matrix.org or #test:localhost:8448. Synapse is currently in rapid development, but as of version 0.5 we believe it is sufficiently stable to be run as an internet-facing service for real usage! Create and manage fully distributed chat rooms with no single points of control or failure. Eventually-consistent cryptographically secure synchronization of room state across a global open network of federated servers and services. Send and receive extensible messages in a room with (optional) end-to-end encryption. ... -
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Brownie
A Python-based development and testing framework for smart contracts
...The recommended way to install Brownie is via pipx. pipx installs Brownie into a virtual environment and makes it available directly from the command-line. Once installed, you will never have to activate a virtual environment prior to using Brownie. Brownie documentation is hosted at Read the Docs. Use tox to run the complete suite against the full set of build targets, or pytest to run tests against a specific version of Python. If you are using pytest you must include the -p no:pytest-brownie flag to prevent it from loading the Brownie plugin. -
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Pocket TTS
A TTS that fits in your CPU (and pocket)
Pocket TTS is a lightweight text-to-speech project designed to run efficiently on CPUs, targeting developers who want local speech generation without depending on GPUs or hosted web APIs. It is built to feel practical in everyday applications, where installation and usage should be as simple as adding a dependency and calling a function. The project focuses on keeping the runtime footprint manageable while still producing natural-sounding speech, which makes it attractive for offline tools, prototypes, and privacy-sensitive workflows. ... -
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Qiskit
Qiskit is an open-source SDK for working with quantum computers
...The transpiler translates Qiskit code into an optimized circuit using a backend’s native gate set, allowing users to program for any quantum processor or processor architecture with minimal inputs. Users can run and schedule jobs on real quantum processors, and employ Qiskit Runtime to orchestrate quantum programs on cloud-based CPUs, QPUs, and GPUs. -
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xonsh
Python-powered, cross-platform, Unix-gazing shell
...The xonsh shell lets you easily mix Python and shell commands in a powerful and simplified approach to the command line. The xonsh language has shell primitives that you are used to from Bash. The xonsh language is a superset of Python 3.6+ and you can run Python code and import modules. With xonsh you can combine Python with shell commands. Prepare environment variables and arguments in Python and use them in shell commands. The language is a superset of Python 3.6+ with additional shell primitives that you are used to from Bash and IPython. -
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Optuna
A hyperparameter optimization framework
Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API. Thanks to our define-by-run API, the code written with Optuna enjoys high modularity, and the user of Optuna can dynamically construct the search spaces for the hyperparameters. Optuna Dashboard is a real-time web dashboard for Optuna. You can check the optimization history, hyperparameter importances, etc. in graphs and tables. ... -
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Simple Evals
Lightweight framework for evaluating large language model performance
simple-evals is a lightweight evaluation framework developed by OpenAI for quickly testing models against small, focused benchmarks. It is designed to help researchers and developers run targeted evaluations without the complexity of large-scale pipelines. By emphasizing simplicity, the framework makes it easy to define new tasks, run evaluations, and interpret results in a reproducible way. It is particularly useful for sanity checks, exploratory research, and comparing performance across different models or configurations. ... -
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Perceval
An open source framework for programming photonic quantum computers
An open-source framework for programming photonic quantum computers. Through a simple object-oriented Python API, Perceval provides tools for composing circuits from linear optical components, defining single-photon sources, manipulating Fock states, running simulations, reproducing published experimental papers and experimenting with a new generation of quantum algorithms. It aims to be a companion tool for developing photonic circuits – for simulating and optimizing their design, modeling... -
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Apache Airflow Provider
Great Expectations Airflow operator
...If your Airflow version is 2.1.0, and you want to install this provider version, first upgrade Airflow to at least version 2.1.0. Otherwise, your Airflow package version will be upgraded automatically, and you will have to manually run airflow upgrade db to complete the migration. This operator currently works with the Great Expectations V3 Batch Request API only. If you would like to use the operator in conjunction with the V2 Batch Kwargs API, you must use a version below 0.1.0. This operator uses Great Expectations Checkpoints instead of the former ValidationOperators. ... -
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Elementary
Open-source data observability for analytics engineers
...Monitoring of data quality metrics, freshness, volume and schema changes, including anomaly detection. Elementary data monitors are configured and executed like native tests in dbt your project. Uploading and modeling of dbt artifacts, run and test results to tables as part of your runs. Get informative notifications on data issues, schema changes, models and tests failures. Inspect upstream and downstream dependencies to understand impact and root cause of data issues. -
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autoresearch
AI agents autonomously run and improve ML experiments overnight
...Designed to run on a single GPU, it keeps the research loop minimal and self-contained to make autonomous experimentation practical. Over time, the agent logs experiments, evaluates improvements, and gradually evolves the model through automated trial-and-error. -
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handy-ollama
Implement CPU from scratch and play with large model deployments
handy-ollama is an open-source educational project designed to help developers and AI enthusiasts learn how to deploy and run large language models locally using the Ollama platform. The repository serves as a structured tutorial that explains how to install, configure, and use Ollama to run modern language models on personal hardware without requiring advanced infrastructure. A key focus of the project is enabling users to run large models even without GPUs by leveraging optimized CPU-based inference pipelines. ... -
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Harbor LLM
Run a full local LLM stack with one command using Docker
...Harbor supports multiple inference engines, including llama.cpp and vLLM, and connects them seamlessly to user interfaces. It also includes tools for web retrieval, image generation, voice interaction, and workflow automation. Built on Docker, Harbor allows services to run in isolated containers while communicating over a local network. It is intended for local development and experimentation rather than production deployment, giving developers a flexible way to explore AI systems, test configurations, and manage complex LLM stacks without manual wiring or setup overhead. -
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Docker SDK for Python
A Python library for the Docker Engine API
Run and manage containers on the server. You can also create more advanced networks with custom IPAM configurations. Get and list nodes in a swarm. Before you can use these methods, you first need to join or initialize a swarm. Manage plugins on the server. Both the main DockerClient and low-level APIClient can connect to the Docker daemon with TLS.
