Showing 2270 open source projects for "python 2"

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  • 1
    openTSNE

    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...
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  • 2
    PipeRider

    PipeRider

    Code review for data in dbt

    ... locally or shared. You can compare two previously generated reports or use a single command to compare the differences between the current branch and the main branch. The latter is designed specifically for code review scenarios. In our pull requests on GitHub, we not only want to know which files have been changed, but also the impact of these changes on the data. PipeRider can easily generate comparison reports with a single command to provide this information.
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  • 3
    llama2-webui

    llama2-webui

    Run any Llama 2 locally with gradio UI on GPU or CPU from anywhere

    Running Llama 2 with gradio web UI on GPU or CPU from anywhere (Linux/Windows/Mac).
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  • 4
    atpbar

    atpbar

    Progress bars for threading and multiprocessing tasks on terminal

    Progress bars for threading and multiprocessing tasks on the terminal and Jupyter Notebook. atpbar can display multiple progress bars simultaneously growing to show the progresses of iterations of loops in threading or multiprocessing tasks. atpbar can display progress bars on the terminal and Jupyter Notebook. atpbar can be used with Mantichora. atpbar started its development in 2015 as part of Alphatwirl. atpbar prevented physicists from terminating their running analysis codes, which...
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  • 5
    Haiku

    Haiku

    JAX-based neural network library

    ... DeepMind. It preserves Sonnet’s module-based programming model for state management while retaining access to JAX’s function transformations. Haiku can be expected to compose with other libraries and work well with the rest of JAX. Similar to Sonnet modules, Haiku modules are Python objects that hold references to their own parameters, other modules, and methods that apply functions on user inputs.
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  • 6
    Granian

    Granian

    A Rust HTTP server for Python applications

    A Rust HTTP server for Python applications. Supports ASGI/3, RSGI and WSGI interface applications. Implements HTTP/1 and HTTP/2 protocols. Supports HTTPS. Supports Websockets over HTTP/1 and HTTP/2.
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  • 7
    unsloth

    unsloth

    Finetune Llama 3.2, Mistral, Phi & Gemma LLMs 2-5x faster

    A productivity tool to enhance team collaboration, focusing on tracking tasks, setting goals, and managing time efficiently.
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  • 8
    TensorFlow Privacy

    TensorFlow Privacy

    Library for training machine learning models with privacy for data

    Library for training machine learning models with privacy for training data. This repository contains the source code for TensorFlow Privacy, a Python library that includes implementations of TensorFlow optimizers for training machine learning models with differential privacy. The library comes with tutorials and analysis tools for computing the privacy guarantees provided.
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  • 9
    Haiku Sonnet for JAX

    Haiku Sonnet for JAX

    JAX-based neural network library

    ..., and a simple function transformation, hk.transform. hk.Modules are Python objects that hold references to their own parameters, other modules, and methods that apply functions on user inputs. hk.transform turns functions that use these object-oriented, functionally "impure" modules into pure functions that can be used with jax.jit, jax.grad, jax.pmap, etc.
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  • 10
    Population Shift Monitoring

    Population Shift Monitoring

    Monitor the stability of a Pandas or Spark dataframe

    popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets. popmon creates histograms of features binned in time-slices, and compares the stability of the profiles and distributions of those histograms using statistical tests, both over time and with respect to a reference. It works with numerical, ordinal, categorical features, and the histograms can be higher-dimensional, e.g. it can also track correlations between any two...
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  • 11
    DeepSpeed MII

    DeepSpeed MII

    MII makes low-latency and high-throughput inference possible

    ... is still restricted by two critical factors: inference latency and cost. DeepSpeed-MII is a new open-source python library from DeepSpeed, aimed towards making low-latency, low-cost inference of powerful models not only feasible but also easily accessible. MII offers access to the highly optimized implementation of thousands of widely used DL models. MII-supported models achieve significantly lower latency and cost compared to their original implementation.
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  • 12
    Fantomas

    Fantomas

    FSharp source code formatter

    F# source code formatter, inspired by scalariform for Scala, ocp-indent for OCaml and PythonTidy for Python. This project aims at formatting F# source files based on a given configuration. Fantomas will ensure correct indentation and consistent spacing between elements in the source files. We assume that the source files are parsable by F# compiler before feeding into the tool. Fantomas follows two F# style guides: the F# code formatting guidelines from Microsoft by default and the G-Research F...
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  • 13
    django-rest-framework-gis

    django-rest-framework-gis

    Geographic add-ons for Django REST Framework

    ... responses but may become an issue for large responses. The primary key of the model (usually the "id" attribute) is automatically used as the id field of each GeoJSON Feature Object. The GeoJSON specification allows a feature to contain a boundingbox of a feature. GeoFeatureModelSerializer allows two different ways to fill this property. The first is using the geo_field to calculate the bounding box of a feature.
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  • 14
    Django RQ

    Django RQ

    A simple app that provides django integration for RQ

    A simple app that provides django integration for RQ (Redis Queue). Django integration with RQ, a Redis-based Python queuing library. Django-RQ is a simple app that allows you to configure your queues in django's settings.py and easily use them in your project. Django-RQ allows you to easily put jobs into any of the queues defined in settings.py. You can provide your own singleton Redis connection object to this function so that it will not create a new connection object for each queue...
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  • 15
    Sweetviz

    Sweetviz

    Visualize and compare datasets, target values and associations

    Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Shows how a target value (e.g. "Survived" in the Titanic...
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  • 16
    Jaeger

    Jaeger

    Monitor and troubleshoot transactions in complex distributed systems

    .... It is used for monitoring and troubleshooting microservices-based distributed systems. OpenTracing compatible data model and instrumentation libraries include Go, Java, Node, Python, C++ and C#. Jaeger uses consistent upfront sampling with individual per service/endpoint probabilities and it has multiple storage backends: Cassandra, Elasticsearch, memory.
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  • 17
    Cinemagoer

    Cinemagoer

    Python package useful to retrieve and manage the data of IMDb

    Cinemagoer (previously known as IMDbPY) is a Python package for retrieving and managing the data of the IMDb movie database about movies and people. You can use the search_movie method of the access object to search for movies with a given (or similar) title. Similarly, you can search for people and companies using the search_person and the search_company methods. Movie, person, and company objects have id attributes which -when fetched through the IMDb web server- store the IMDb id...
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  • 18
    Recurrent Interface Network (RIN)

    Recurrent Interface Network (RIN)

    Implementation of Recurrent Interface Network (RIN)

    ... for larger images. The big surprise is that the generations can reach this level of fidelity. Will need to verify this on my own machine. Additionally, we will try adding an extra linear attention on the main branch as well as self-conditioning in the pixel space. The insight of being able to self-condition on any hidden state of the network as well as the newly proposed sigmoid noise schedule are the two main findings.
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  • 19
    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...
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  • 20
    AIMET

    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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  • 21
    OpenCLIP

    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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  • 22
    Thinc

    Thinc

    A refreshing functional take on deep learning

    ..., configure and deploy custom models built with their favorite framework. Switch between PyTorch, TensorFlow and MXNet models without changing your application, or even create mutant hybrids using zero-copy array interchange. Develop faster and catch bugs sooner with sophisticated type checking. Trying to pass a 1-dimensional array into a model that expects two dimensions? That’s a type error. Your editor can pick it up as the code leaves your fingers.
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  • 23
    data-diff

    data-diff

    Efficiently diff rows across two different databases

    We're excited to announce the launch of a new open-source product, data-diff that makes comparing datasets across databases fast at any scale. data-diff automates data quality checks for data replication and migration. In modern data platforms, data is constantly moving between systems, and at the modern data volume and complexity, systems go out of sync all the time. Until now, there has not been any tooling to ensure that when the data is correctly copied. Replicating data at scale, across...
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  • 24
    Flagsmith

    Flagsmith

    Open source feature flagging and remote config service

    ... toggles across web, mobile, and server-side applications. Just wrap a section of code with a flag, and then use Flagsmith to manage that feature. Manage feature flags by the development environment, and for individual users, a segment of users, or a percentage. This means quickly implementing practices like canary deployments. Multivariate flags allow you to use a percentage split across two or more variations for precise A/B/n testing and experimentation.
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  • 25
    tsfresh

    tsfresh

    Automatic extraction of relevant features from time series

    tsfresh is a python package. It automatically calculates a large number of time series characteristics, the so called features. tsfresh is used to to extract characteristics from time series. Without tsfresh, you would have to calculate all characteristics by hand. With tsfresh this process is automated and all your features can be calculated automatically. Further tsfresh is compatible with pythons pandas and scikit-learn APIs, two important packages for Data Science endeavours in python...
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