Search Results for "xp windows linux" - Page 6
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Showing 487 open source projects for "xp windows linux"
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SageMaker Hugging Face Inference Toolkit
Library for serving Transformers models on Amazon SageMaker
SageMaker Hugging Face Inference Toolkit is an open-source library for serving Transformers models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain Transformers models and tasks. It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging... -
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peepDB
CLI tool and python library to inspect databases fast
peepDB is an open-source command-line tool and Python library designed for developers and database administrators who need a fast and efficient way to inspect their database tables without writing SQL queries. With support for MySQL, PostgreSQL, and MariaDB, peepDB is lightweight, secure, and incredibly easy to use. -
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Malicious PDF Generator
Generate a bunch of malicious pdf files with phone-home functionality
Generate ten different malicious PDF files with phone-home functionality. Can be used with Burp Collaborator or Interact.sh. Used for penetration testing and/or red-teaming etc. I created this tool because I needed a third-party tool to generate a bunch of PDF files with various links. -
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Otter-Grader
A Python and R autograding solution
Otter Grader is a light-weight, modular open-source autograder developed by the Data Science Education Program at UC Berkeley. It is designed to work with classes at any scale by abstracting away the autograding internals in a way that is compatible with any instructor's assignment distribution and collection pipeline. Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment of an... -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
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Kami
Good content deserves good paper
Kami is a minimalistic productivity tool designed to help users organize tasks, notes, and daily workflows in a clean and distraction-free interface. It focuses on simplicity, enabling users to capture ideas quickly and manage them efficiently without unnecessary complexity. The application is built with a modern design philosophy that emphasizes clarity and usability. It supports lightweight task management and note-taking features for personal productivity. Kami is suitable for users who... -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before... -
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GraalPy
A Python 3 implementation built on GraalVM
GraalPy is a high-performance implementation of the Python language for the JVM built on GraalVM. GraalPy is a Python 3.11 compliant runtime. It has first-class support for embedding in Java and can turn Python applications into fast, standalone binaries. GraalPy is ready for production running pure Python code and has experimental support for many popular native extension modules. -
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jlens
Companion code for the global workspace interpretability paper
Jacobian Lens is Anthropic’s reference implementation for examining what a language model’s internal activations are inclined to produce as text. It transports residual-stream vectors from selected layers and positions into the final-layer basis using an averaged input-output Jacobian. The transformed vectors are decoded through the model’s own unembedding into ranked vocabulary predictions. The package can fit new lenses, load saved ones, apply them to prompts, and merge results from... -
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Claude for Legal
A suite of plugins for legal workflows
Claude for Legal is a suite of reference agents, skills, and connectors built to support common legal workflows with Claude. It is designed for in-house teams, law firms, clinics, and legal students who need structured assistance across commercial, corporate, employment, privacy, product, litigation, regulatory, AI governance, and IP work. The project can run as a Claude plugin or through Claude’s Managed Agents API, giving teams flexibility in how they deploy the same prompts and skills.... -
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Tree
tree is a library for working with nested data structures
Tree (dm-tree) is a lightweight Python library developed by Google DeepMind for manipulating nested data structures (also called pytrees). It generalizes Python’s built-in map function to operate over arbitrarily nested collections — including lists, tuples, dicts, and custom container types — while preserving their structure. This makes it particularly useful in machine learning pipelines and JAX-based workflows, where complex parameter trees or hierarchical state representations are... -
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Comprehensive Python Cheatsheet
Comprehensive Python Cheatsheet
Comprehensive Python Cheatsheet is a comprehensive reference resource that consolidates essential Python syntax, idioms, and best practices into a highly readable and searchable format. The project is designed to help developers quickly recall language features without digging through full documentation, making it especially useful for both beginners and experienced programmers. It covers a broad range of topics including data structures, control flow, functions, object-oriented programming,... -
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Copy Fail - CVE-2026-31431
epository that demonstrates and analyzes a Linux kernel vulnerability
Copy Fail - CVE-2026-31431 is a proof-of-concept repository that demonstrates and analyzes a specific Linux kernel vulnerability identified as CVE-2026-31431. The project provides experimental scripts and documentation to reproduce and study the exploit in controlled environments. It is designed for security researchers and engineers who want to understand the mechanics of the vulnerability. The repository includes tested configurations across multiple Linux distributions and kernel... -
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PageIndex
Document Index for Vectorless, Reasoning-based RAG
PageIndex is an innovative open-source framework that reimagines retrieval-augmented generation (RAG) by eliminating conventional vector similarity search and instead building hierarchical semantic indexes that mirror a document’s natural structure. Rather than chunking text and embedding it into a vector database, PageIndex constructs a tree-structured index — similar to a detailed, AI-enhanced table of contents — that a large language model can traverse to locate the most relevant sections... -
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Recursive Language Models
General plug-and-play inference library for Recursive Language Models
RLM (short for Reinforcement Learning Models) is a modular framework that makes it easier to build, train, evaluate, and deploy reinforcement learning (RL) agents across a wide range of environments and tasks. It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom... -
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Stock prediction deep neural learning
Predicting stock prices using a TensorFlow LSTM
Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. Predicting stock... -
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Flax
Flax is a neural network library for JAX
Flax is a flexible neural-network library for JAX that embraces functional programming while offering ergonomic module abstractions. Its design separates pure computation from state by threading parameter collections and RNGs explicitly, enabling reproducibility, transformation, and easy experimentation with JAX transforms like jit, pmap, and vmap. Modules define parameterized computations, but initialization and application remain side-effect free, which pairs naturally with JAX’s staging... -
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Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major... -
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PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,... -
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JC
CLI tool and python library
CLI tool and python library that converts the output of popular command-line tools and file types to JSON or Dictionaries. This allows piping of output to tools like jq and simplifying automation scripts. jc JSONifies the output of many CLI tools and file types for easier parsing in scripts. This allows further command-line processing of output with tools like jq or jello by piping commands. The JC parsers can also be used as python modules. In this case, the output will be a python... -
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Werkzeug
The comprehensive WSGI web application library
Werkzeug is a comprehensive WSGI web application library. It began as a simple collection of various utilities for WSGI applications and has become one of the most advanced WSGI utility libraries. Werkzeug doesn’t enforce any dependencies. It is up to the developer to choose a template engine, database adapter, and even how to handle requests. Includes an interactive debugger that allows inspecting stack traces and source code in the browser with an interactive interpreter for any frame in... -
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mosdepth
fast BAM/CRAM depth calculation for WGS, exome, or targeted sequencing
mosdepth is a fast BAM/CRAM depth calculation tool for genomic data, allowing efficient computation of sequencing coverage. -
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py2many
Transpiler of Python to many other languages
Python is popular, and easy to program in, but it has poor runtime performance. We can fix that by transpiring a subset of the language into a more performant, statically typed language. A second benefit is security. Writing security-sensitive code in a low-level language like C is error-prone and could lead to privilege escalation. Specialized languages such as wuffs exist to address this use case. py2many can be a more general-purpose solution to the problem where you can verify the source... -
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Recommenders 2023
Best Practices on Recommendation Systems
Recommenders objective is to assist researchers, developers and enthusiasts in prototyping, experimenting with and bringing to production a range of classic and state-of-the-art recommendation systems. Recommenders is a project under the Linux Foundation of AI and Data. -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior...