Search Results for "metasploitable-2" - Page 4
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Showing 2994 open source projects for "metasploitable-2"
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openTSNE
Extensible, parallel implementations of t-SNE
openTSNE is a modular Python implementation of t-Distributed Stochasitc Neighbor Embedding (t-SNE) [1], a popular dimensionality-reduction algorithm for visualizing high-dimensional data sets. openTSNE incorporates the latest improvements to the t-SNE algorithm, including the ability to add new data points to existing embeddings [2], massive speed improvements [3] [4] [5], enabling t-SNE to scale to millions of data points, and various tricks to improve the global alignment of the resulting visualizations. -
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WordOps
Install and manage a high performance WordPress stack
An essential toolset that eases WordPress site and server administration. -
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Pants Build System
The Pants Build System
Pants 2 is a fast, scalable, user-friendly build system for codebases of all sizes. It's currently focused on Python, Go, Java, Scala, Kotlin, Shell, and Docker, with support for other languages and frameworks coming soon. A lot of effort has gone into making Pants easy to adopt, easy to use and easy to extend. We're super excited to bring Pants' distinctive features to Go, Java, Python, Scala, Kotlin, and Shell users. -
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PyMuPDF
Python bindings for MuPDF's rendering library.
...It renders text with metrics and spacing accurate to within fractions of a pixel for the highest fidelity in reproducing the look of a printed page on the screen. The viewer is small, fast, yet complete. It supports many document formats, such as PDF, XPS, OpenXPS, CBZ, EPUB, and FictionBook 2. You can annotate PDF documents and fill out forms with the mobile viewers (this feature is coming soon to the desktop viewer as well). The command line tools allow you to annotate, edit, and convert documents to other formats such as HTML, SVG, PDF, and CBZ. You can also write scripts to manipulate documents using Javascript. The library is written modularly in portable C, so features can be added and removed by integrators if they so desire. -
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Kitten TTS
State-of-the-art TTS model under 25MB
KittenTTS is an open-source, ultra-lightweight, and high-quality text-to-speech model featuring just 15 million parameters and a binary size under 25 MB. It is designed for real-time CPU-based deployment across diverse platforms. Ultra-lightweight, model size less than 25MB. CPU-optimized, runs without GPU on any device. High-quality voices, several premium voice options available. Fast inference, optimized for real-time speech synthesis. -
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LLaMA 3
The official Meta Llama 3 GitHub site
...Even as a deprecated repo, it documents the transition path and preserves references that clarify how Llama 3 releases map into the current ecosystem. Practically, it functioned as a bridge between Llama 2 and later Llama releases by standardizing distribution and starter code for inference and fine-tuning. Teams still treat it as historical reference material for version lineage and migration notes. -
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Selectolax
Python binding to Modest and Lexbor engines
A fast HTML5 parser with CSS selectors using Modest and Lexbor engines. Selectolax supports two backends: Modest and Lexbor. By default, all examples use the Modest backend. Most of the features between backends are almost identical, but there are still some differences. Currently, the Lexbor backend is in beta and missing some of the features. To use lexbor, just import the parser and use it in the similar way to the HTMLParser. -
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Mistral Inference
Official inference library for Mistral models
...We release open-weight models for everyone to customize and deploy where they want it. Our super-efficient model Mistral Nemo is available under Apache 2.0, while Mistral Large 2 is available through both a free non-commercial license, and a commercial license. -
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parallel-ssh
Asynchronous parallel SSH client library.
parallel-ssh is an asynchronous parallel SSH library designed for large-scale automation. It differentiates itself from alternatives, other libraries and higher-level frameworks like Ansible or Chef in several ways. -
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OpenLLM
Operating LLMs in production
...With OpenLLM, you can run inference with any open-source large-language models, deploy to the cloud or on-premises, and build powerful AI apps. Built-in supports a wide range of open-source LLMs and model runtime, including Llama 2， StableLM, Falcon, Dolly, Flan-T5, ChatGLM, StarCoder, and more. Serve LLMs over RESTful API or gRPC with one command, query via WebUI, CLI, our Python/Javascript client, or any HTTP client. -
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AIMET
AIMET is a library that provides advanced quantization and compression
Qualcomm Innovation Center (QuIC) is at the forefront of enabling low-power inference at the edge through its pioneering model-efficiency research. QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware... -
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Denoising Diffusion Probabilistic Model
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to generative modeling that may have the potential to rival GANs. It uses denoising score matching to estimate the gradient of the data distribution, followed by Langevin sampling to sample from the true distribution. If you simply want to pass in a folder name and the desired image dimensions, you can use the Trainer class to easily train a model. -
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Typer
Typer, build great CLIs, based on Python type hints
...Automatic help, and automatic completion for all shells. Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs. The simplest example adds only 2 lines of code to your app: 1 import, 1 function call. Grow in complexity as much as you want, create arbitrarily complex trees of commands and groups of subcommands, with options and arguments. And it's intended to be the FastAPI of CLIs. Typer stands on the shoulders of a giant. Its only internal dependency is Click. -
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Unsloth Studio
Unified web UI for training and running open models locally
Unsloth Studio is a web-based interface for running and training AI models locally with a unified and user-friendly experience. It allows users to work with a wide range of models for text, audio, vision, embeddings, and more without relying heavily on cloud infrastructure. Built on top of the Unsloth framework, it focuses on high-performance training with reduced VRAM usage and faster speeds compared to traditional methods. The platform supports fine-tuning, pretraining, and reinforcement... -
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Pylint
It's not just a linter that annoys you!
Pylint is a static code analyzer for Python 2 or 3. The latest version supports Python 3.7.2 and above. Pylint analyses your code without actually running it. It checks for errors, enforces a coding standard, looks for code smells, and can make suggestions about how the code could be refactored. Projects that you might want to use alongside pylint include flake8 (faster and simpler checks with very few false positives), mypy, pyright or pyre (typing checks), bandit (security-oriented checks), black and isort (auto-formatting), autoflake (automated removal of unused import or variable), pyupgrade (automated upgrade to newer python syntax) and pydocstringformatter (automated pep257). ... -
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UForm
Multi-Modal Neural Networks for Semantic Search, based on Mid-Fusion
...Early-fusion models encode both modalities jointly so they can take into account fine-grained features. Usually, these models are used for re-ranking relatively small retrieval results. Mid-fusion models are the golden midpoint between the previous two types. Mid-fusion models consist of two parts – unimodal and multimodal. -
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GLM-TTS
Controllable & emotion-expressive zero-shot TTS
GLM-TTS is an advanced text-to-speech synthesis system built on large language model technologies that focuses on producing high-quality, expressive, and controllable spoken output, including features like emotion modulation and zero-shot voice cloning. It uses a two-stage architecture where a generative LLM first converts text into intermediate speech token sequences and then a Flow-based neural model converts those tokens into natural audio waveforms, enabling rich prosody and voice character even for unseen speakers. The system introduces a multi-reward reinforcement learning framework that jointly optimizes for voice similarity, emotional expressiveness, pronunciation, and intelligibility, yielding output that can rival commercial options in naturalness and expressiveness. ... -
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Aim
An easy-to-use & supercharged open-source experiment tracker
...If you'd like to modify the integration and make it custom, create a new integration package and share with others. Aim is an open-source, self-hosted AI Metadata tracking tool designed to handle 100,000s of tracked metadata sequences. The two most famous AI metadata applications are: experiment tracking and prompt engineering. Aim provides a performant and beautiful UI for exploring and comparing training runs, and prompt sessions. -
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DoWhy
DoWhy is a Python library for causal inference
...DoWhy provides a wide variety of algorithms for effect estimation, causal structure learning, diagnosis of causal structures, root cause analysis, interventions and counterfactuals. DoWhy builds on two of the most powerful frameworks for causal inference: graphical causal models and potential outcomes. For effect estimation, it uses graph-based criteria and do-calculus for modeling assumptions and identifying a non-parametric causal effect. For estimation, it switches to methods based primarily on potential outcomes. -
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Remarshal
Convert between CBOR, JSON, MessagePack, TOML, and YAML
Convert between CBOR, JSON, MessagePack, TOML, and YAML. When installed, provides the command-line command remarshal as well as the short commands {cbor,json,msgpack,toml,yaml}2{cbor,json,msgpack,toml,yaml}. You can perform format conversion, reformatting, and error detection using these commands. CBOR, MessagePack, and YAML with binary fields cannot be converted to JSON or TOML. Binary fields are converted between CBOR, MessagePack, and YAML. -
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nginx-proxy
Automated nginx proxy for Docker containers using docker-gen
nginx-proxy sets up a container running nginx and docker-gen. docker-gen generates reverse proxy configs for nginx and reloads nginx when containers are started and stopped. The containers being proxied must expose the port to be proxied, either by using the EXPOSE directive in their Dockerfile or by using the --expose flag to docker run or docker create and be in the same network. By default, if you don't pass the --net flag when your nginx-proxy container is created, it will only be... -
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GHunt
Offensive Google framework
...It's currently focused on OSINT, but any use related with Google is possible. It will automatically use venvs to avoid dependency conflicts with other projects. First, launch the listener by doing ghunt login and choose between 1 of the 2 first methods. Put GHunt on listening mode (currently not compatible with docker) Paste base64-encoded cookies. Enter manually all cookies. The development of this extension has followed Firefox guidelines to use the Promise-based WebExtension/BrowserExt API being standardized by the W3 Browser Extensions group, and is using webextension-polyfill to provide cross-browser compatibility with no changes. -
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uvloop
Ultra fast asyncio event loop
...Together with asyncio and the power of async/await in Python 3.5, uvloop makes it easier than ever to write high-performance Python networking code. uvloop makes asyncio incredibly fast-- 2 to 4 times faster than nodejs, or any other Python asynchronous framework. The performance of asyncio when it is uvloop-based is almost comparable to that of Go programs. uvloop is written in Cython and is built on top of libuv, a high performance, fast and stable multiplatform asynchronous I/O library used by nodejs. -
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OpenCLIP
An open source implementation of CLIP
The goal of this repository is to enable training models with contrastive image-text supervision and to investigate their properties such as robustness to distribution shift. Our starting point is an implementation of CLIP that matches the accuracy of the original CLIP models when trained on the same dataset. Specifically, a ResNet-50 model trained with our codebase on OpenAI's 15 million image subset of YFCC achieves 32.7% top-1 accuracy on ImageNet. OpenAI's CLIP model reaches 31.3% when... -
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ClearML
Streamline your ML workflow
...It is designed as an end-to-end MLOps suite allowing you to focus on developing your ML code & automation, while ClearML ensures your work is reproducible and scalable. The ClearML Python Package for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments and other workflows with ClearML powerful and versatile set of classes and methods. The ClearML Server storing experiment, model, and workflow data, and supports the Web UI experiment manager, and ML-Ops automation for reproducibility and tuning. It is available as a hosted service and open source for you to deploy your own ClearML Server. ...
