Search Results for "per linux"
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Showing 104 open source projects for "per linux"
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Atera all-in-one platform IT management software with AI agentsAtera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
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Retool your internal operationsBuild internal software that meets enterprise security standards without waiting on engineering resources. Retool connects to your databases, APIs, and data sources while maintaining the permissions and controls you need. Create custom dashboards, admin tools, and workflows from natural language prompts—all deployed in your cloud with security baked in. Stop duct-taping operations together, start building in Retool.
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Telegram Media Downloader
Download media files from a telegram conversation/chat/channel
Download media files from a telegram conversation/chat/channel up to 2GiB per file. -
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DeepSeek R1
Open-source, high-performance AI model with advanced reasoning
DeepSeek-R1 is an open-source large language model developed by DeepSeek, designed to excel in complex reasoning tasks across domains such as mathematics, coding, and language. DeepSeek R1 offers unrestricted access for both commercial and academic use. The model employs a Mixture of Experts (MoE) architecture, comprising 671 billion total parameters with 37 billion active parameters per token, and supports a context length of up to 128,000 tokens. DeepSeek-R1's training regimen uniquely... -
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DeepSeek-V3
Powerful AI language model (MoE) optimized for efficiency/performance
DeepSeek-V3 is a robust Mixture-of-Experts (MoE) language model developed by DeepSeek, featuring a total of 671 billion parameters, with 37 billion activated per token. It employs Multi-head Latent Attention (MLA) and the DeepSeekMoE architecture to enhance computational efficiency. The model introduces an auxiliary-loss-free load balancing strategy and a multi-token prediction training objective to boost performance. Trained on 14.8 trillion diverse, high-quality tokens, DeepSeek-V3... -
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Moltbot
Your own personal AI assistant. Any OS. Any Platform.
Moltbot is an open-source, local-first personal AI assistant designed to run on your own devices while staying fast, private, and always available. It connects seamlessly to the communication channels you already use, including popular messaging apps, collaboration tools, and web chat interfaces. Instead of being a cloud-hosted bot, Moltbot centers around a local Gateway that acts as the control plane, making the assistant feel responsive and under your control. It supports advanced... -
Find Hidden Risks in Windows Task SchedulerWindows Task Scheduler might be hiding critical failures. Download the free JAMS diagnostic tool to uncover problems before they impact production—get a color-coded risk report with clear remediation steps in minutes.
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UCO3D
Uncommon Objects in 3D dataset
uCO3D is a large-scale 3D vision dataset and toolkit centered on turn-table videos of everyday objects drawn from the LVIS taxonomy. It provides about 170,000 full videos per object instance rather than still frames, along with per-video annotations including object masks, calibrated camera poses, and multiple flavors of point clouds. Each sequence also ships with a precomputed 3D Gaussian Splat reconstruction, enabling fast, differentiable rendering workflows and modern implicit/point-based... -
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HunyuanImage-3.0
A Powerful Native Multimodal Model for Image Generation
HunyuanImage-3.0 is a powerful, native multimodal text-to-image generation model released by Tencent’s Hunyuan team. It unifies multimodal understanding and generation in a single autoregressive framework, combining text and image modalities seamlessly rather than relying on separate image-only diffusion components. It uses a Mixture-of-Experts (MoE) architecture with many expert subnetworks to scale efficiently, deploying only a subset of experts per token, which allows large parameter... -
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MiMo-V2-Flash
MiMo-V2-Flash: Efficient Reasoning, Coding, and Agentic Foundation
MiMo-V2-Flash is a large Mixture-of-Experts language model designed to deliver strong reasoning, coding, and agentic-task performance while keeping inference fast and cost-efficient. It uses an MoE setup where a very large total parameter count is available, but only a smaller subset is activated per token, which helps balance capability with runtime efficiency. The project positions the model for workflows that require tool use, multi-step planning, and higher throughput, rather than only... -
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WavTokenizer
SOTA discrete acoustic codec models with 40/75 tokens per second
WavTokenizer is a state-of-the-art discrete acoustic codec designed specifically for audio language modeling, capable of compressing 24 kHz audio into just 40 or 75 tokens per second while preserving high perceptual quality. It is built to represent speech, music, and general audio with extremely low bitrate, making it ideal as a front-end for large audio language models like GPT-4o and similar architectures. The model uses a single-quantizer design together with temporal compression to... -
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MyChatGPT
OSS standalone ChatGPT client
This is a OSS standalone ChatGPT client. It is based on ChatGPT. The client works almost just like the original ChatGPT websites but it includes some additional features. I wanted to use ChatGPT but I didn't want to pay a fixed price if I have days where I barely use it. So I created this client that almost works like the original. The 20 dollar price tag on ChatGPT is a bit steep for me. I don't want to pay for a service I don't use. I also don't want to pay for a service that I use only a... -
Rent Manager SoftwareRent Manager is award-winning property management software built for residential, commercial, and short-term-stay portfolios of any size. The program’s fully customizable features include a double-entry accounting system, maintenance management/scheduling, marketing integration, mobile applications, more than 450 insightful reports, and an API that integrates with the best PropTech providers on the market.
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EasyVoice
Open source text-to-speech tool, supports extra-long text
easyVoice is an open-source text-to-speech platform aimed at turning long-form text and novels into high-quality audio, with a strong focus on usability and scalability. It provides a web interface where users can paste or upload large texts and generate speech and subtitles in a single workflow, even for works exceeding 100,000 characters. The system supports multi-role voice acting, letting users assign different neural voices to different characters or narrative roles and configure... -
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kener
Kener is a Modern Self hosted Status Page, batteries included
Kener: Open-source Node.js status page tool, designed to make service monitoring and incident handling a breeze. It offers a sleek and user-friendly interface that simplifies tracking service outages and improves how we communicate during incidents. And the best part? Kener integrates seamlessly with GitHub, making incident management a team effort—making it easier for us to track and fix issues together in a collaborative and friendly environment. -
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Style-Bert-VITS2
Style-Bert-VITS2: Bert-VITS2 with more controllable voice styles
Style-Bert-VITS2 is a text-to-speech system based on Bert-VITS2 that focuses on highly controllable voice styles and emotional expression. It takes the original Bert-VITS2 v2.1 and its Japanese-Extra variant and extends them so you can control emotion and speaking style with fine-grained intensity, not just choose a generic tone. The project targets both power users and beginners: Windows users without Git or Python can install and run it using bundled .bat scripts, while advanced users can... -
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MiniMax-M2
MiniMax-M2, a model built for Max coding & agentic workflows
MiniMax-M2 is an open-weight large language model designed specifically for high-end coding and agentic workflows while staying compact and efficient. It uses a Mixture-of-Experts (MoE) architecture with 230 billion total parameters but only 10 billion activated per token, giving it the behavior of a very large model at a fraction of the runtime cost. The model is tuned for end-to-end developer flows such as multi-file edits, compile–run–fix loops, and test-validated repairs across real... -
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VGGT
[CVPR 2025 Best Paper Award] VGGT
VGGT is a transformer-based framework aimed at unifying classic visual geometry tasks—such as depth estimation, camera pose recovery, point tracking, and correspondence—under a single model. Rather than training separate networks per task, it shares an encoder and leverages geometric heads/decoders to infer structure and motion from images or short clips. The design emphasizes consistent geometric reasoning: outputs from one head (e.g., correspondences or tracks) reinforce others (e.g., pose... -
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tslearn
The machine learning toolkit for time series analysis in Python
The machine learning toolkit for time series analysis in Python. tslearn expects a time series dataset to be formatted as a 3D numpy array. The three dimensions correspond to the number of time series, the number of measurements per time series and the number of dimensions respectively (n_ts, max_sz, d). In order to get the data in the right format. -
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FileScope MCP
Analyzes your codebase identifying important files based on dependency
FileScopeMCP is a TypeScript-based tool that analyzes codebases to identify important files based on dependency relationships. It generates diagrams and importance scores per file, aiding in understanding code structure and assisting AI assistants in navigating complex projects. -
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Octelium
A next-gen FOSS self-hosted unified zero trust secure access platform
Octelium is an open source, self-hosted unified secure-access platform built for modern infrastructure and hybrid environments. It positions itself as more than a typical VPN; it supports zero-trust network access (ZTNA), “BeyondCorp”-style access, API/AI gateway functionality, and even serves as a PaaS-like deployment surface. One of its key strengths is identity-based, application-layer (L7) aware control, meaning access decisions are made per request, with context and policy rather than... -
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MiniMax-01
Large-language-model & vision-language-model based on Linear Attention
MiniMax-01 is the official repository for two flagship models: MiniMax-Text-01, a long-context language model, and MiniMax-VL-01, a vision-language model built on top of it. MiniMax-Text-01 uses a hybrid attention architecture that blends Lightning Attention, standard softmax attention, and Mixture-of-Experts (MoE) routing to achieve both high throughput and long-context reasoning. It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel... -
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InfiniteYou
Flexible Photo Recrafting While Preserving Your Identity
InfiniteYou is an open-source image-generation and “identity-preserving image editing / generation” framework from ByteDance, designed to generate high-fidelity images that preserve a subject’s identity while allowing flexible editing or re-creation according to textual prompts. Using an architecture built around diffusion transformers (DiTs), InfiniteYou introduces a component called InfuseNet that injects identity features derived from reference images into the generation process — via... -
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Monoio
Rust async runtime based on io-uring
Monoio is a Rust asynchronous runtime designed for high-performance I/O-bound servers and applications, built around native OS async I/O primitives (e.g. io_uring on Linux, epoll / kqueue on other Unix-like systems), rather than layering atop an existing runtime. Its design philosophy centers on a “thread-per-core” model where each core runs its own event loop, minimizing cross-thread synchronization needs, avoiding the overhead and complexity of task scheduling, and letting developers write efficient, low-overhead asynchronous networking or I/O code. ... -
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SHAP
A game theoretic approach to explain the output of ml models
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions. While SHAP can explain the output of any machine learning model, we have developed a high-speed exact algorithm for tree ensemble methods. Fast C++ implementations are supported for XGBoost, LightGBM, CatBoost, scikit-learn and pyspark... -
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SetFit
Efficient few-shot learning with Sentence Transformers
SetFit is an efficient and prompt-free framework for few-shot fine-tuning of Sentence Transformers. It achieves high accuracy with little labeled data - for instance, with only 8 labeled examples per class on the Customer Reviews sentiment dataset, SetFit is competitive with fine-tuning RoBERTa Large on the full training set of 3k examples. -
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3FS
A high-performance distributed file system
The 3FS repository (standing likely for “Feature 3F System” or similar) is focused on providing a feature extraction and transformation framework tailored to deep and large models, especially in token-based systems. Its primary aim is to support efficient and scalable feature transformation pipelines—especially for inference environments—by batching, caching, and integrating feature-based modules like segmenters, sparse retrievers, and scorers seamlessly. The repo includes APIs to define... -
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Auto Synced & Translated Dubs
Automatically translates the text of a video based on a subtitle file
Auto-Synced-Translated-Dubs is a toolchain that automatically translates and re-dubs videos using AI voices while keeping the new speech aligned to the original timing via subtitle files. It assumes you have a human-made SRT (or similar) subtitle file; the script then uses translation services such as Google Cloud or DeepL to generate translated subtitle tracks in one or more target languages. Using the timestamps of each subtitle line, it computes the required duration of each spoken... -
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FLAML
A fast library for AutoML and tuning
FLAML is a lightweight Python library that finds accurate machine learning models automatically, efficiently and economically. It frees users from selecting learners and hyperparameters for each learner. For common machine learning tasks like classification and regression, it quickly finds quality models for user-provided data with low computational resources. It supports both classical machine learning models and deep neural networks. It is easy to customize or extend. Users can find their...
