Showing 318 open source projects for "order"

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  • 1
    DeepSeek-OCR 2

    DeepSeek-OCR 2

    Visual Causal Flow

    DeepSeek-OCR-2 is the second-generation optical character recognition system developed to improve document understanding by introducing a “visual causal flow” mechanism, enabling the encoder to reorder visual tokens in a way that better reflects semantic structure rather than strict raster scan order. It is designed to handle complex layouts and noisy documents by giving the model causal reasoning capabilities that mimic human visual scanning behavior, enhancing OCR performance on documents with rich spatial structure. The repository provides model code and inference scripts that let researchers and developers run and benchmark the system on both images and PDFs, with support for batch evaluation and optimized pipelines leveraging vLLM and transformers.
    Downloads: 1 This Week
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  • 2
    Shapash

    Shapash

    Explainability and Interpretability to Develop Reliable ML models

    Shapash is a Python library dedicated to the interpretability of Data Science models. It provides several types of visualization that display explicit labels that everyone can understand. Data Scientists can more easily understand their models, share their results and easily document their projects in an HTML report. End users can understand the suggestion proposed by a model using a summary of the most influential criteria.
    Downloads: 0 This Week
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  • 3
    python-bibtexparser v2

    python-bibtexparser v2

    Bibtex parser for Python 3

    Welcome to python-bibtexparser, a parser for .bib files with a long history and wide adaption. Bibtexparser is available in two versions: V1 and V2. For new projects, we recommend using v2 which, in the long run, will provide an overall more robust and faster experience. For now, however, note that v2 is an early beta, and does not contain all features of v1.
    Downloads: 0 This Week
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  • 4
    NautilusTrader

    NautilusTrader

    A high-performance algorithmic trading platform

    NautilusTrader is an open-source, high-performance, production-grade algorithmic trading platform, provides quantitative traders with the ability to backtest portfolios of automated trading strategies on historical data with an event-driven engine, and also deploy those same strategies live, with no code changes. The platform is 'AI-first', designed to develop and deploy algorithmic trading strategies within a highly performant and robust Python native environment. This helps to address the...
    Downloads: 4 This Week
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  • 5
    JAX

    JAX

    Composable transformations of Python+NumPy programs

    ...It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order. What’s new is that JAX uses XLA to compile and run your NumPy programs on GPUs and TPUs. Compilation happens under the hood by default, with library calls getting just-in-time compiled and executed. But JAX also lets you just-in-time compile your own Python functions into XLA-optimized kernels using a one-function API, jit. Compilation and automatic differentiation can be composed arbitrarily, so you can express sophisticated algorithms and get maximal performance without leaving Python.
    Downloads: 4 This Week
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  • 6
    marimo

    marimo

    A reactive notebook for Python

    ...Version with git, run as Python scripts, import symbols from a notebook into other notebooks or Python files, and lint or format with your favorite tools. You'll always be able to reproduce your collaborators' results. Notebooks are executed in a deterministic order, with no hidden state, delete a cell and marimo deletes its variables while updating affected cells.
    Downloads: 2 This Week
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  • 7
    Pyper

    Pyper

    Concurrent Python made simple

    Pyper is a Python-native orchestration and scheduling framework designed for modern data workflows, machine learning pipelines, and any task that benefits from a lightweight DAG-based execution engine. Unlike heavier platforms like Airflow, Pyper aims to remain lean, modular, and developer-friendly, embracing Pythonic conventions and minimizing boilerplate. It focuses on local development ergonomics and seamless transition to production environments, making it ideal for small teams and...
    Downloads: 0 This Week
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  • 8
    Dough

    Dough

    Dough is a open source tool for steering AI animations with precision

    We believe that AI has the potential to allow billions to experience creative fulfillment this century. However, in order to reach this potential, artistic control is key - it's the difference between something feeling like it was made by you rather than for you. To unlock the multitude of control types and artistic flows possible with AI, we want to build tooling and infrastructure to empower a community of tool-builders, who in turn empower a world of budding artists.
    Downloads: 0 This Week
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  • 9
    Agent SOP

    Agent SOP

    Natural language workflows for AI agents

    Agent SOP is a framework that implements structured operational procedures (SOPs) for autonomous agents so that they can carry out complex multi-step tasks reliably and in a defined order. Instead of relying solely on broad language model reasoning, this project enforces explicit step sequences with checkpoints, conditional transitions, and rollback logic, making agent workflows more predictable and auditable. It defines reusable SOP templates that agents can instantiate with context-specific parameters, allowing organizations to codify best practices for customer support, data processing, document workflows, or incident response. ...
    Downloads: 1 This Week
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  • 10
    Perf Book

    Perf Book

    The book "Performance Analysis and Tuning on Modern CPU"

    This project is a practical guide to performance analysis and tuning on modern CPUs, bridging microarchitecture details with hands-on profiling. It explains how caches, TLBs, prefetchers, branch predictors, and out-of-order execution influence real program speed, then connects those concepts to concrete optimization strategies. Readers learn how to design trustworthy benchmarks, avoid measurement traps (warmup, turbo, frequency scaling), and interpret hardware performance counters. The book walks through vectorization, memory layout, data-oriented design, and algorithmic choices, illustrating when compiler flags, intrinsics, or hand-rolled assembly make sense. ...
    Downloads: 1 This Week
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  • 11
    Docling

    Docling

    Get your documents ready for gen AI

    ...The project focuses on converting and parsing many document formats into a unified structured representation that downstream systems can easily consume. It supports advanced PDF understanding, including layout detection, table extraction, and reading order analysis, enabling high-fidelity document intelligence pipelines. Docling is designed to run efficiently on commodity hardware and can be used both as a Python API and a command-line tool. Its modular architecture allows developers to extend functionality and integrate specialized models for tasks such as OCR and audio transcription. ...
    Downloads: 0 This Week
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  • 12
    TurboDiffusion

    TurboDiffusion

    100–200× Acceleration for Video Diffusion Models

    TurboDiffusion is an advanced open-source framework designed to dramatically accelerate video diffusion model generation, aiming for performance improvements on the order of 100–200× compared with traditional implementations while retaining high output quality. It achieves this by combining a suite of algorithmic and engineering optimizations, including attention acceleration techniques, efficient step distillation methods, and quantization strategies that reduce computational overhead. The project targets large video models and enables developers to run accelerated generation even on single high-end GPUs, making fast video synthesis more practical for research and creative workflows. ...
    Downloads: 0 This Week
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  • 13
    Optax

    Optax

    Optax is a gradient processing and optimization library for JAX

    Optax is a gradient processing and optimization library for JAX. It is designed to facilitate research by providing building blocks that can be recombined in custom ways in order to optimize parametric models such as, but not limited to, deep neural networks. We favor focusing on small composable building blocks that can be effectively combined into custom solutions. Others may build upon these basic components in more complicated abstractions. Whenever reasonable, implementations prioritize readability and structuring code to match standard equations, over code reuse.
    Downloads: 0 This Week
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  • 14
    bbox-visualizer

    bbox-visualizer

    Make drawing and labeling bounding boxes easy as cake

    ...There are optional functions that can draw multiple bounding boxes and/or write multiple labels on the same image, but it is advisable to use the above functions in a loop in order to have full control over your visualizations.
    Downloads: 0 This Week
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  • 15
    django-import-export

    django-import-export

    Django application and library for importing and exporting data

    ...Also, the report_skipped option controls whether skipped records appear in the import Result object, and if using the admin whether skipped records will show in the import preview page. Not all data can be easily extracted from an object/model attribute. In order to turn complicated data model into a (generally simpler) processed data structure on export, dehydrate_<fieldname> method should be defined.
    Downloads: 0 This Week
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  • 16
    dots.ocr

    dots.ocr

    Multilingual Document Layout Parsing in a Single Vision-Language Model

    dots.ocr is a cutting-edge multilingual document parsing system built on a unified vision-language model that combines layout detection, text recognition, and structural understanding into a single architecture. Unlike traditional OCR pipelines that rely on multiple specialized components, dots.ocr integrates these processes end-to-end, reducing error propagation and improving consistency across tasks. The model is designed to recognize virtually any human script, making it highly effective...
    Downloads: 0 This Week
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  • 17
    Quantitative Trading System

    Quantitative Trading System

    A comprehensive quantitative trading system with AI-powered analysis

    Quantitative Trading System is a comprehensive quantitative trading platform that integrates artificial intelligence, financial data analysis, and automated strategy execution within a unified software system. The project is designed to provide an end-to-end infrastructure for building and operating algorithmic trading strategies in financial markets. It includes tools for collecting and processing market data from multiple sources, performing statistical and machine learning analysis, and...
    Downloads: 0 This Week
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  • 18
    Apache Hamilton

    Apache Hamilton

    Helps data scientists define testable self-documenting dataflows

    ...Hamilton automatically analyzes these functions and constructs a directed acyclic graph representing the pipeline, allowing the system to execute transformations in the correct order. This approach encourages modular, testable, and maintainable data pipelines because each transformation is isolated and easily unit tested. The framework also automatically tracks lineage and metadata about how data is produced, which improves debugging, reproducibility, and transparency in data workflows.
    Downloads: 0 This Week
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  • 19
    LLMs-Zero-to-Hero

    LLMs-Zero-to-Hero

    From nobody to big model (LLM) hero

    ...The repository presents a structured learning pathway that begins with fundamental concepts in machine learning and progresses toward advanced topics such as model pre-training, fine-tuning, and deployment. Rather than relying entirely on existing frameworks, the project encourages readers to implement important components themselves in order to gain a deeper understanding of how modern language models work internally. It includes explanations of dense transformer architectures, mixture-of-experts models, training pipelines, and techniques used in contemporary LLM development.
    Downloads: 0 This Week
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  • 20
    WeClone

    WeClone

    One-stop solution for creating your digital avatar from chat history

    WeClone is an open source AI project designed to replicate a person’s conversational style and personality by training models on chat history data. The system analyzes message patterns, linguistic style, and contextual behavior in order to generate responses that resemble the original user’s communication style. It is intended primarily as an experimental exploration of digital personality modeling and conversational AI personalization. By processing large volumes of conversation data, WeClone can build a profile of an individual’s writing tone, vocabulary preferences, and conversational tendencies. ...
    Downloads: 0 This Week
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  • 21
    gplearn

    gplearn

    Genetic Programming in Python, with a scikit-learn inspired API

    ...It begins by building a population of naive random formulas to represent a relationship between known independent variables and their dependent variable targets in order to predict new data. Each successive generation of programs is then evolved from the one that came before it by selecting the fittest individuals from the population to undergo genetic operations.
    Downloads: 0 This Week
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  • 22
    AtomAI

    AtomAI

    Deep and Machine Learning for Microscopy

    AtomAI is a Pytorch-based package for deep and machine-learning analysis of microscopy data that doesn't require any advanced knowledge of Python or machine learning. The intended audience is domain scientists with a basic understanding of how to use NumPy and Matplotlib. It was developed by Maxim Ziatdinov at Oak Ridge National Lab. The purpose of the AtomAI is to provide an environment that bridges the instrument-specific libraries and general physical analysis by enabling the seamless...
    Downloads: 0 This Week
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  • 23
    GemGIS

    GemGIS

    Spatial data processing for geomodeling

    ...It is capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages,…), raster data (tif, png,…), data obtained from online services (WCS, WMS, WFS) or XML/KML files (soon). Preprocessed data can be stored in a dedicated Data Class to be passed to the geomodeling package GemPy in order to accelerate the model-building process. Postprocessing of model results will allow export from GemPy to geoinformation systems such as QGIS and ArcGIS or to Google Earth for further use.
    Downloads: 0 This Week
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  • 24
    Trafilatura

    Trafilatura

    Python & command-line tool to gather text on the Web

    ...Going from raw HTML to essential parts can alleviate many problems related to text quality, first by avoiding the noise caused by recurring elements (headers, footers, links/blogroll etc.) and second by including information such as author and date in order to make sense of the data. The extractor tries to strike a balance between limiting noise (precision) and including all valid parts (recall). It also has to be robust and reasonably fast, it runs in production on millions of documents.
    Downloads: 0 This Week
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  • 25
    OpenWPM

    OpenWPM

    A web privacy measurement framework

    OpenWPM is a web privacy measurement framework that makes it easy to collect data for privacy studies on a scale of thousands to millions of websites. OpenWPM is built on top of Firefox, with automation provided by Selenium. It includes several hooks for data collection. Check out the instrumentation section below for more details. OpenWPM is tested on Ubuntu 18.04 via TravisCI and is commonly used via the docker container that this repo builds, which is also based on Ubuntu. Although we...
    Downloads: 0 This Week
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