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Showing 2587 open source projects for "open ssh windows"
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TurboQuant+
Implementation of TurboQuant (ICLR 2026)
TurboQuant Plus is an extended and enhanced version of quantization tooling aimed at improving neural network efficiency through advanced compression and optimization strategies. It builds upon the concept of reducing model precision to accelerate inference while attempting to maintain or recover accuracy through refined techniques. The project explores additional enhancements such as improved calibration, adaptive quantization, and potentially hybrid precision approaches that combine... -
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NVIDIA Model Optimizer
A unified library of SOTA model optimization techniques
Model Optimizer is a unified library that provides state-of-the-art techniques for compressing and optimizing deep learning models to improve inference efficiency and deployment performance. It brings together multiple optimization strategies such as quantization, pruning, distillation, and speculative decoding into a single cohesive framework. The library is designed to reduce model size and computational requirements while maintaining accuracy, making it particularly valuable for deploying... -
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Finance
150+ quantitative finance Python programs
Finance is a repository that compiles structured notes and educational material related to financial analysis, markets, and quantitative finance concepts. The project focuses on explaining key principles used in finance and investment analysis, including topics such as financial statements, valuation models, portfolio theory, and financial markets. The repository is designed as a study reference for students and professionals who want to understand financial systems and the analytical... -
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Pixeltable
Data Infrastructure providing an approach to multimodal AI workloads
Pixeltable is an open-source Python data infrastructure framework designed to support the development of multimodal AI applications. The system provides a declarative interface for managing the entire lifecycle of AI data pipelines, including storage, transformation, indexing, retrieval, and orchestration of datasets. Unlike traditional architectures that require multiple tools such as databases, vector stores, and workflow orchestrators, Pixeltable unifies these functions within a... -
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AppAgent
Multimodal Agents as Smartphone Users, an LLM-based multimodal agent
AppAgent is an open-source multimodal agent framework designed to enable large language models to operate smartphone applications through natural interactions with graphical user interfaces. The system allows an AI agent to interpret visual information from the screen and translate natural language instructions into actions such as tapping, swiping, and navigating between application screens. Instead of requiring backend access to application APIs, the framework interacts with apps the same... -
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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... -
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HunyuanWorld 1.0
Generating Immersive, Explorable, and Interactive 3D Worlds
HunyuanWorld-1.0 is an open-source, simulation-capable 3D world generation model developed by Tencent Hunyuan that creates immersive, explorable, and interactive 3D environments from text or image inputs. It combines the strengths of video-based diversity and 3D-based geometric consistency through a novel framework using panoramic world proxies and semantically layered 3D mesh representations. This approach enables 360° immersive experiences, seamless mesh export for graphics pipelines, and... -
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Simple StyleGan2 for Pytorch
Simplest working implementation of Stylegan2
Simple Pytorch implementation of Stylegan2 that can be completely trained from the command-line, no coding needed. You will need a machine with a GPU and CUDA installed. You can also specify the location where intermediate results and model checkpoints should be stored. You can increase the network capacity (which defaults to 16) to improve generation results, at the cost of more memory. By default, if the training gets cut off, it will automatically resume from the last checkpointed file.... -
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Pytorch-toolbelt
PyTorch extensions for fast R&D prototyping and Kaggle farming
A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images. Every-day common routines (fix/restore random seed, filesystem utils, metrics). Losses:... -
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Deep Agents
The batteries-included agent harness
Deep Agents is an open-source, batteries-included agent harness designed for long-running, multi-step AI work. It provides an opinionated agent setup while allowing developers to override or replace individual pieces without forking the project. The framework is model-agnostic and works with tool-calling models from hosted providers, open-weight deployments, or local runtimes. Built on LangGraph, it includes persistence, checkpointing, streaming, and production-oriented orchestration. Agents... -
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DataProfiler
Extract schema, statistics and entities from datasets
DataProfiler is an AI-powered tool for automatic data analysis and profiling, designed to detect patterns, anomalies, and schema inconsistencies in structured and unstructured datasets. The DataProfiler is a Python library designed to make data analysis, monitoring, and sensitive data detection easy. Loading Data with a single command, the library automatically formats & loads files into a DataFrame. Profiling the Data, the library identifies the schema, statistics, entities (PII / NPI), and... -
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Continuous Claude v3
Context management for Claude Code. Hooks maintain state via ledgers
Continuous Claude v3 is a persistent, multi-agent development environment built around the Claude Code CLI that aims to overcome the limitations of standard LLM context windows. Rather than relying on a single session’s context, Continuous Claude uses mechanisms like ledgers, YAML handoffs, and a memory system to preserve and recall state across multiple sessions, ensuring that learned insights and plans are not lost when context compaction occurs. The project orchestrates many specialized... -
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fireworks-tech-graph
Claude Code skill for generating production-quality SVG+PNG technical
fireworks-tech-graph is an AI-driven project focused on building structured knowledge graphs that map relationships between technologies, concepts, and entities within technical domains. It aims to transform unstructured information into interconnected graphs that can be queried and analyzed for insights, making it easier to understand complex ecosystems such as software stacks or research fields. The system likely leverages AI techniques for entity extraction, relationship mapping, and... -
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Basic Memory
Persistent AI memory using local Markdown knowledge graphs
Basic Memory is an open source knowledge system that turns AI conversations into persistent, structured knowledge you control. Instead of losing context after each chat, it stores information as simple Markdown files on your device, allowing both you and AI to read and write to the same knowledge base. It uses the Model Context Protocol (MCP) so compatible AI tools can access, update, and build on your notes across sessions. Basic Memory creates a semantic knowledge graph by linking related... -
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DeepAnalyze
Autonomous LLM agent for end-to-end data science workflows
DeepAnalyze is an open source project that introduces an agentic large language model designed to perform autonomous data science tasks from start to finish. It is built to handle the entire data science pipeline, including data preparation, analysis, modeling, visualization, and report generation without requiring continuous human guidance. DeepAnalyze is capable of conducting open-ended data research across multiple data formats such as structured tables, semi-structured files, and... -
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autoMate
AI tool for automating desktop tasks via natural language input
autoMate is an AI-powered local automation tool designed to enable users to control and automate their computers using natural language instructions instead of traditional scripting or rule-based systems. It combines large language models with computer vision techniques to interpret user intent and understand on-screen content, allowing it to interact with graphical interfaces similarly to a human user. autoMate follows an observe-decide-act workflow, where it analyzes the screen, plans... -
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OpenSandbox
OpenSandbox is a general-purpose sandbox platform for AI applications
OpenSandbox is a general purpose sandbox platform designed to securely run and isolate AI applications and untrusted workloads in controlled environments. The project focuses on providing a unified sandbox API that simplifies the process of executing code safely across different runtime backends. It supports multiple programming languages through SDKs, allowing developers to integrate sandbox capabilities into their systems without building custom isolation layers. The platform is built to... -
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Claude Agent SDK for Python
Python SDK for Claude Agent
Claude Agent SDK (Python) is the official Python counterpart to the TypeScript Agent SDK from Anthropic, designed to let Python developers build powerful autonomous AI agents with Claude Code under the hood. The SDK wraps the core functionality of Claude Code and exposes high-level asynchronous and synchronous interfaces to query prompts, manage sessions, and orchestrate tool use — so you can build agents that understand code, make edits, run bash commands, interact with files, and handle... -
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HY-MT
Hunyuan Translation Model Version 1.5
HY-MT (Hunyuan Translation) is a high-quality multilingual machine translation model suite developed to support mutual translation across dozens of languages with strong performance even at smaller model scales. It ships with both an 1.8 B parameter model and a larger 7 B model, the latter optimized not only for direct translation but also for formatted and contextualized output, allowing better handling of terminology and mixed-language content. The project emphasizes both speed and... -
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OuteTTS
Interface for OuteTTS models
OuteTTS is an interface library for running OuteTTS text-to-speech models across a range of backends, making it easier to deploy the same model on different hardware and runtimes. It provides a high-level Interface API that wraps model configuration, speaker handling, and audio generation so you can focus on integrating speech into your application rather than wiring up low-level engines. The project supports multiple backends including llama.cpp (Python bindings and server), Hugging Face... -
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Real-Time Voice Cloning
Clone a voice in 5 seconds to generate arbitrary speech in real-time
Real-Time Voice Cloning is an influential deep-learning repository that demonstrates how to clone a voice from just a few seconds of audio and then generate arbitrary speech in that voice in near real time. It implements the SV2TTS pipeline (“Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis”) in three stages: a speaker encoder, a synthesizer, and a vocoder. In the first stage, short audio clips are converted into a fixed-dimensional speaker embedding that... -
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Janus
Unified Multimodal Understanding and Generation Models
Janus is a sophisticated open-source project from DeepSeek AI that aims to unify both visual understanding and image generation in a single model architecture. Rather than having separate systems for “look and describe” and “prompt and generate”, Janus uses an autoregressive transformer framework with a decoupled visual encoder—allowing it to ingest images for comprehension and to produce images from text prompts with shared internal representations. The design tackles long-standing... -
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HumanEval
Code for the paper "Evaluating Large Language Models Trained on Code"
human-eval is a benchmark dataset and evaluation framework created by OpenAI for measuring the ability of language models to generate correct code. It consists of hand-written programming problems with unit tests, designed to assess functional correctness rather than superficial metrics like text similarity. Each task includes a natural language prompt and a function signature, requiring the model to generate an implementation that passes all provided tests. The benchmark has become a... -
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Kaldi
kaldi-asr/kaldi is the official location of the Kaldi project
Kaldi is an open source toolkit for speech recognition research. It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to... -
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Langroid
Harness LLMs with Multi-Agent Programming
Given the remarkable abilities of recent Large Language Models (LLMs), there is an unprecedented opportunity to build intelligent applications powered by this transformative technology. The top question for any enterprise is: how best to harness the power of LLMs for complex applications? For technical and practical reasons, building LLM-powered applications is not as simple as throwing a task at an LLM system and expecting it to do it. Effectively leveraging LLMs at scale requires a...
