Search Results for "x-windows" - Page 45
Sort By:
Showing 2650 open source projects for "x-windows"
View related business solutions-
$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.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
Atropos
Language Model Reinforcement Learning Environments frameworks
Atropos is a comprehensive open-source framework for reinforcement learning (RL) environments tailored specifically to work with large language models (LLMs). Designed as a scalable ecosystem of environment microservices, Atropos allows researchers and developers to collect, evaluate, and manage trajectories (sequences of actions and outcomes) generated by LLMs across a variety of tasks—from static dataset benchmarks to dynamic interactive games and real-world scenario environments. It... -
2
D4RL
Collection of reference environments, offline reinforcement learning
D4RL (Datasets for Deep Data-Driven Reinforcement Learning) is a benchmark suite focused on offline reinforcement learning — i.e., learning policies from fixed datasets rather than via online interaction with the environment. It contains standardized environments, tasks and datasets (observations, actions, rewards, terminals) aimed at enabling reproducible research in offline RL. Researchers can load a dataset for a given task (e.g., maze navigation, manipulation) and apply their algorithm... -
3
Minigrid
Simple and easily configurable grid world environments
Minigrid is a lightweight, minimalistic grid-world environment library for reinforcement learning (RL) research. It provides a suite of simple 2D grid-based tasks (e.g., navigating mazes, unlocking doors, carrying keys) where an agent moves in discrete steps and interacts with objects. The design emphasizes speed (agents can run thousands of steps per second), low dependency overhead, and high customizability — making it easy to define new maps, new tasks, or wrappers. It supports the... -
4
plexe
Build a machine learning model from a prompt
plexe lets you build machine-learning systems from natural-language prompts, turning plain English goals into working pipelines. You describe what you want—a predictor, a classifier, a forecaster—and the tool plans data ingestion, feature preparation, model training, and evaluation automatically. Under the hood an agent executes the plan step by step, surfacing intermediate results and artifacts so you can inspect or override choices. It aims to be production-minded: models can be exported,... -
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.
-
5
llm.c
LLM training in simple, raw C/CUDA
llm.c is a minimalist, systems-level implementation of a small transformer-based language model in C that prioritizes clarity and educational value. By stripping away heavy frameworks, it exposes the core math and memory flows of embeddings, attention, and feed-forward layers. The code illustrates how to wire forward passes, losses, and simple training or inference loops with direct control over arrays and buffers. Its compact design makes it easy to trace execution, profile hotspots, and... -
6
UltraRAG
Less Code, Lower Barrier, Faster Deployment
UltraRAG 2.0 is a low-code, MCP-enabled RAG framework that aims to lower the barrier to building complex retrieval pipelines for research and production. It provides end-to-end recipes—from encoding and indexing corpora to deploying retrievers and LLMs—so users can reproduce baselines and iterate rapidly. The toolkit comes with built-in support for popular RAG datasets, large corpora, and canonical baselines, plus documentation that walks from “quick start” to debugging and case analysis. It... -
7
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,... -
8
MobileCLIP
Implementation of "MobileCLIP" CVPR 2024
MobileCLIP is a family of efficient image-text embedding models designed for real-time, on-device retrieval and zero-shot classification. The repo provides training, inference, and evaluation code for MobileCLIP models trained on DataCompDR, and for newer MobileCLIP2 models trained on DFNDR. It includes an iOS demo app and Core ML artifacts to showcase practical, offline photo search and classification on iPhone-class hardware. Project notes highlight latency/accuracy trade-offs, with... -
9
CutLER
Code release for Cut and Learn for Unsupervised Object Detection
CutLER is an approach for unsupervised object detection and instance segmentation that trains detectors without human-annotated labels, and the repo also includes VideoCutLER for unsupervised video instance segmentation. The method follows a “Cut-and-LEaRn” recipe: bootstrap object proposals, refine them iteratively, and train detection/segmentation heads to discover objects across diverse datasets. The codebase provides training and inference scripts, model configs, and references to... -
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.
-
10
Sapiens
High-resolution models for human tasks
Sapiens is a research framework from Meta AI focused on embodied intelligence and human-like multimodal learning, aiming to train agents that can perceive, reason, and act in complex environments. It integrates sensory inputs such as vision, audio, and proprioception into a unified learning architecture that allows agents to understand and adapt to their surroundings dynamically. The project emphasizes long-horizon reasoning and cross-modal grounding—connecting language, perception, and... -
11
SlowFast
Video understanding codebase from FAIR for reproducing video models
SlowFast is a video understanding framework that captures both spatial semantics and temporal dynamics efficiently by processing video frames at two different temporal resolutions. The slow pathway encodes semantic context by sampling frames sparsely, while the fast pathway captures motion and fine temporal cues by operating on densely sampled frames with fewer channels. Together, these two pathways complement each other, allowing the network to model both appearance and motion without... -
12
CLIP
CLIP, Predict the most relevant text snippet given an image
CLIP (Contrastive Language-Image Pretraining) is a neural model that links images and text in a shared embedding space, allowing zero-shot image classification, similarity search, and multimodal alignment. It was trained on large sets of (image, caption) pairs using a contrastive objective: images and their matching text are pulled together in embedding space, while mismatches are pushed apart. Once trained, you can give it any text labels and ask it to pick which label best matches a given... -
13
Ling
Ling is a MoE LLM provided and open-sourced by InclusionAI
Ling is a Mixture-of-Experts (MoE) large language model (LLM) provided and open-sourced by inclusionAI. The project offers different sizes (Ling-lite, Ling-plus) and emphasizes flexibility and efficiency: being able to scale, adapt expert activation, and perform across a range of natural language/reasoning tasks. Example scripts, inference pipelines, and documentation. The codebase includes inference, examples, models, documentation, and model download infrastructure. As more developers and... -
14
AReal
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible
AReaL is an open source, fully asynchronous reinforcement learning training system. AReal is designed for large reasoning and agentic models. It works with models that perform reasoning over multiple steps, agents interacting with environments. It is developed by the AReaL Team at Ant Group (inclusionAI) and builds upon the ReaLHF project. Release of training details, datasets, and models for reproducibility. It is intended to facilitate reproducible RL training on reasoning / agentic tasks,... -
15
Hunyuan3D-1
A Unified Framework for Text-to-3D and Image-to-3D Generation
Hunyuan3D-1 is an earlier version in the same 3D generation line (the unified framework for text-to-3D and image-to-3D tasks) by Tencent Hunyuan. It provides a framework combining shape generation and texture synthesis, enabling users to create 3D assets from images or text conditions. While less advanced than version 2.1, it laid the foundations for the later PBR, higher resolution, and open-source enhancements. (Note: less detailed public documentation was found for Hunyuan3D-1 compared to... -
16
HunyuanCustom
Multimodal-Driven Architecture for Customized Video Generation
HunyuanCustom is a multimodal video customization framework by Tencent Hunyuan, aimed at generating customized videos featuring particular subjects (people, characters) under flexible conditions, while maintaining subject/identity consistency. It supports conditioning via image, audio, video, and text, and can perform subject replacement in videos, generate avatars speaking given audio, or combine multiple subject images. The architecture builds on HunyuanVideo, with added modules for... -
17
Omnara
Talk to Your AI Agents from Anywhere
Omnara is an open-source agent control platform that empowers developers to turn autonomous AI tools (e.g., Claude Code, Cursor, GitHub Copilot) into collaborative teammates by offering real-time dashboards, push notifications, and remote guidance across terminals, web, and mobile. Omnara transforms your AI agents (Claude Code, Codex CLI, n8n, and more) from silent workers into communicative teammates. Get real-time visibility into what your agents are doing, and respond to their questions... -
18
Agno
Lightweight framework for building Agents with memory, knowledge, etc.
Agno is a modular, open-source artificial general intelligence (AGI) research platform that allows developers to build, evaluate, and experiment with cognitive architectures in a composable way. It provides a flexible framework for modeling reasoning, memory, decision-making, and planning, aimed at long-term AI research beyond narrow learning. Agno embraces multi-agent environments and symbolic reasoning as part of its core design, enabling experiments with structured knowledge,... -
19
Stable Virtual Camera
Stable Virtual Camera: Generative View Synthesis with Diffusion Models
Stable Virtual Camera is a multi-view diffusion model developed by Stability AI that transforms 2D images into immersive 3D videos with realistic depth and perspective. Unlike traditional methods that require complex reconstruction or scene-specific optimization, this model allows users to generate novel views from any number of input images and define custom camera trajectories, enabling dynamic exploration of scenes. It supports various aspect ratios and can produce 3D-consistent videos up... -
20
aisuite
Simple, unified interface to multiple Generative AI providers
Simple, unified interface to multiple Generative AI providers. aisuite makes it easy for developers to use multiple LLM through a standardized interface. Using an interface similar to OpenAI's, aisuite makes it easy to interact with the most popular LLMs and compare the results. It is a thin wrapper around Python client libraries and allows creators to seamlessly swap out and test responses from different LLM providers without changing their code. Today, the library is primarily focused on... -
21
Superduper
Superduper: Integrate AI models and machine learning workflows
Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This... -
22
NeMo Curator
Scalable data pre processing and curation toolkit for LLMs
NeMo Curator is a Python library specifically designed for fast and scalable dataset preparation and curation for large language model (LLM) use-cases such as foundation model pretraining, domain-adaptive pretraining (DAPT), supervised fine-tuning (SFT) and paramter-efficient fine-tuning (PEFT). It greatly accelerates data curation by leveraging GPUs with Dask and RAPIDS, resulting in significant time savings. The library provides a customizable and modular interface, simplifying pipeline... -
23
Taipy
Turns Data and AI algorithms into production-ready web applications
From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability. Taipy enhances performance with caching control of graphical events, optimizing rendering by selectively updating graphical components only upon interaction. Effortlessly manage massive datasets with Taipy's built-in decimator for charts, intelligently reducing the number of data points to save time and memory without losing the essence of your data's shape.... -
24
CAMEL AI
Finding the Scaling Law of Agents. A multi-agent framework
The rapid advancement of conversational and chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conversation, which can be challenging and time-consuming. This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents and provide insight into their "cognitive" processes. To address the challenges of achieving autonomous... -
25
Bytewax
Python Stream Processing
Bytewax is a Python framework that simplifies event and stream processing. Because Bytewax couples the stream and event processing capabilities of Flink, Spark, and Kafka Streams with the friendly and familiar interface of Python, you can re-use the Python libraries you already know and love. Connect data sources, run stateful transformations, and write to various downstream systems with built-in connectors or existing Python libraries. Bytewax is a Python framework and Rust distributed...
