Search Results for "pam-python" - Page 70
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Showing 19356 open source projects for "pam-python"
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proxy.py
Utilize all available CPU cores for accepting new client connections
proxy.py is made with performance in mind. By default, proxy.py will try to utilize all available CPU cores to it for accepting new client connections. This is achieved by starting AcceptorPool which listens on configured server port. Then, AcceptorPool starts Acceptor processes (--num-acceptors) to accept incoming client connections. Alongside, if --threadless is enabled, ThreadlessPool is setup which starts Threadless processes (--num-workers) to handle the incoming client connections.... -
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requests-cache
Persistent HTTP cache for python requests
requests-cache is a persistent HTTP cache that provides an easy way to get better performance with the Python requests library. Keep using the requests library you’re already familiar with. Add caching with a drop-in replacement for requests. The session, or install globally to add transparent caching to all request functions. Get sub-millisecond response times for cached responses. When they expire, you still save time with conditional requests. -
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amrlib
A python library that makes AMR parsing, generation and visualization
A python library that makes AMR parsing, generation and visualization simple. amrlib is a python module designed to make processing for Abstract Meaning Representation (AMR) simple by providing the following functions. Sentence to Graph (StoG) parsing to create AMR graphs from English sentences. Graph to Sentence (GtoS) generation for turning AMR graphs into English sentences. -
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AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference,... -
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Kubespray
Deploy a Production Ready Kubernetes Cluster
Can be deployed on AWS, GCE, Azure, OpenStack, vSphere, Equinix Metal (bare metal), Oracle Cloud Infrastructure (Experimental), or Baremetal. Highly available cluster. Composable (Choice of the network plugin for instance). Supports most popular Linux distributions. Continuous integration tests. The list of available docker versions is 18.09, 19.03, and 20.10. The recommended docker version is 20.10. The kubelet might break on docker's non-standard version numbering (it no longer uses... -
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PyTorch Ignite
Library to help with training and evaluating neural networks
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. Less code than pure PyTorch while ensuring maximum control and simplicity. Library approach and no program's control inversion. Use ignite where and when you need. Extensible API for metrics, experiment managers, and other components. The cool thing with handlers is that they offer unparalleled flexibility (compared to, for example, callbacks). Handlers can be any function: e.g.... -
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openpilot
Open source driver assistance system
openpilot is an open-source driver assistance system designed to improve upon the existing driver assistance of most modern cars today. openpilot gives you Tesla Autopilot-like functionality with functions like Adaptive Cruise Control (ACC), Automated Lane Centering (ALC), Forward Collision Warning (FCW) and Lane Departure Warning (LDW). All these with just a push of a button. openpilot also includes a camera-based driver monitoring feature that alerts distracted and asleep drivers while it... -
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Exploitarium
A single archive of public exploit PoCs and vulnerability research
Exploitarium is a consolidated archive of public proof-of-concept vulnerability research and exploit writeups. It gathers older standalone research repositories into one place while also adding newer entries as self-contained folders. The project includes tracked examples involving software such as 7-Zip, AnyDesk, c-ares, curl, Discourse, Docker, and other targets. Its purpose is research visibility, vulnerability study, and educational review rather than normal application deployment.... -
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NVIDIA NeMo Agent Toolkit
Library for efficiently connecting and optimizing teams of AI agents
NVIDIA NeMo Agent Toolkit is an open-source framework designed to build, optimize, and manage AI agents across different development ecosystems. It provides enterprise-grade tools for improving agent performance, reliability, and observability throughout the development lifecycle. The toolkit integrates with popular agent frameworks such as LangChain, LlamaIndex, CrewAI, Microsoft Semantic Kernel, and Google ADK. Developers can monitor agent execution, trace workflows, and analyze... -
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AudioMuse-AI
AudioMuse-AI is an Open Source Dockerized environment
AudioMuse-AI is an open-source system designed to automatically generate playlists and analyze music libraries using artificial intelligence and audio signal processing techniques. The platform runs locally in a Dockerized environment and performs detailed sonic analysis on audio files to understand characteristics such as tempo, mood, and acoustic similarity. By analyzing the underlying audio content rather than relying on external metadata services, the system can organize large personal... -
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Google Workspace MCP Server
Control Gmail, Google Calendar, Docs, Sheets, Slides, Chat, Forms
Google Workspace MCP is an open-source server that connects AI assistants to Google Workspace services through the Model Context Protocol (MCP), allowing large language models to interact directly with productivity tools. The project exposes a wide set of Google services including Gmail, Google Drive, Docs, Sheets, Slides, Calendar, Chat, and other Workspace components as structured tools that an AI system can call programmatically. By acting as a bridge between AI clients and the Google... -
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Streamer-Sales
LLM Large Model of Selling Anchor
Streamer-Sales is an open-source large language model system designed specifically for e-commerce live streaming and automated product promotion. The project focuses on generating persuasive product descriptions and live presentation scripts that mimic the style of professional online sales hosts. By analyzing product characteristics and marketing information, the model can produce engaging explanations that emphasize benefits, features, and emotional appeal to encourage viewers to make... -
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Google Toolbox for Mac
Google Toolbox for Mac
Google Toolbox for Mac (GTMSession) is a comprehensive collection of open source Objective-C utilities and frameworks developed by Google to support macOS and iOS application development. It consolidates reusable code components drawn from various internal Google projects, offering developers a wide range of tools for building efficient, maintainable Apple platform software. The library includes modules for networking, logging, testing, data handling, and user interface extensions, helping... -
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OpenAI Harmony
Renderer for the harmony response format to be used with gpt-oss
Harmony is a response format developed by OpenAI for use with the gpt-oss model series. It defines a structured way for language models to produce outputs, including regular text, reasoning traces, tool calls, and structured data. By mimicking the OpenAI Responses API, Harmony provides developers with a familiar interface while enabling more advanced capabilities such as multiple output channels, instruction hierarchies, and tool namespaces. The format is essential for ensuring gpt-oss... -
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PaLM + RLHF - Pytorch
Implementation of RLHF (Reinforcement Learning with Human Feedback)
PaLM-rlhf-pytorch is a PyTorch implementation of Pathways Language Model (PaLM) with Reinforcement Learning from Human Feedback (RLHF). It is designed for fine-tuning large-scale language models with human preference alignment, similar to OpenAI’s approach for training models like ChatGPT. -
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MiniSom
MiniSom is a minimalistic implementation of the Self Organizing Maps
MiniSom is a minimalistic and Numpy-based implementation of the Self Organizing Maps (SOM). SOM is a type of Artificial Neural Network able to convert complex, nonlinear statistical relationships between high-dimensional data items into simple geometric relationships on a low-dimensional display. Minisom is designed to allow researchers to easily build on top of it and to give students the ability to quickly grasp its details. The project initially aimed for a minimalistic implementation of... -
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BudouX
Standalone, small, language-neutral
Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning-powered line break organizer tool. It is standalone. It works with no dependency on third-party word segmenters such as Google cloud natural language API. It is small. It takes only around 15 KB including its machine learning model. It's reasonable to use it even on the client-side. It is language-neutral. You can train a model for any language by feeding a dataset to BudouX’s training... -
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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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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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Claude Plugins Community
Community plugin marketplace for Claude Cowork and Claude Code
Claude Plugins — Community is a read-only marketplace repository for community-contributed plugins compatible with Claude Cowork and Claude Code. It acts as the public mirror of Anthropic’s reviewed community plugin catalog. The marketplace metadata is synchronized nightly from Anthropic’s internal review pipeline. Listed plugins have passed automated security scanning and approval before distribution. Claude Code users can add the repository as a marketplace and install individual community... -
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X4G
Fast and modern gateway for VLESS tunneling on WebSocket and XHTTP
X4G is a self-hosted gateway for operating VLESS tunnels over WebSocket and two XHTTP transport modes. It also includes an internal HTTP proxy for clients that need a conventional proxy endpoint. A web dashboard displays service statistics, hourly traffic charts, live connections, activity records, and error logs. Administrators can create unlimited connection links with individual traffic quotas, bandwidth limits, expiration dates, ports, and simultaneous IP restrictions. Subscription... -
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JamTools
JamTools is a cross-platform gadget set software
JamTools is a multifunctional desktop utility suite designed to provide a collection of tools for productivity, media processing, and system enhancements within a single application. It integrates various features such as file management, multimedia handling, and system utilities into a unified interface. The project emphasizes ease of use while offering advanced functionality for handling common tasks efficiently. It includes support for media-related operations, often leveraging FFmpeg for... -
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caveman
Why use many token when few token do trick
Caveman is a lightweight and experimental project focused on simplifying backend or full-stack development workflows through minimalistic abstractions and rapid prototyping principles. It is designed to reduce the complexity of modern frameworks by offering a stripped-down approach that prioritizes speed, clarity, and ease of use. The project often serves as a foundation for developers who want to build applications quickly without being constrained by heavy conventions or extensive... -
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Book4_Power-of-Matrix
Book_4_Matrix Power | The Iris Book: From Addition, Subtraction
...The project is designed to help readers progress from basic arithmetic toward machine learning fundamentals by building a strong conceptual understanding of vectors, matrices, and their operations. It combines explanatory text, diagrams, and Python examples to bridge theory and practical computation. The material emphasizes geometric interpretation and visual reasoning, which makes abstract linear algebra topics more accessible to beginners and self-learners. The repository is continuously updated and intended to accompany the broader Visualize-ML learning ecosystem. Overall, it serves as a visually driven mathematical foundation for students preparing for data science and machine learning work. -
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The Data Engineering Handbook
Links to everything you'd ever want to learn about data engineering
The Data Engineering Handbook is a comprehensive, community-curated repository that aggregates essential learning resources for anyone interested in becoming a professional data engineer. Rather than being a code project itself, it’s a learning handbook that links to books, articles, tutorials, community groups, boot camps, and real-world project examples that collectively form a roadmap to mastering data engineering skills. It includes beginner and intermediate boot camps, interview guides,...
