Showing 1637 open source projects for "compiler python linux"

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  • 1
    Lazy Predict

    Lazy Predict

    Lazy Predict help build a lot of basic models without much code

    Lazy Predict helps build a lot of basic models without much code and helps understand which models work better without any parameter tuning.
    Downloads: 0 This Week
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  • 2
    KerasTuner

    KerasTuner

    A Hyperparameter Tuning Library for Keras

    KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily configure your search space with a define-by-run syntax, then leverage one of the available search algorithms to find the best hyperparameter values for your models. KerasTuner comes with Bayesian Optimization, Hyperband, and Random Search algorithms built-in, and is also designed to be easy for researchers to extend in order to experiment with new search...
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  • 3
    pomegranate

    pomegranate

    Fast, flexible and easy to use probabilistic modelling in Python

    pomegranate is a library for probabilistic modeling defined by its modular implementation and treatment of all models as the probability distributions they are. The modular implementation allows one to easily drop normal distributions into a mixture model to create a Gaussian mixture model just as easily as dropping a gamma and a Poisson distribution into a mixture model to create a heterogeneous mixture. But that's not all! Because each model is treated as a probability distribution,...
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  • 4
    Featuretools

    Featuretools

    An open source python library for automated feature engineering

    An open source Python framework for automated feature engineering. Featuretools automatically creates features from temporal and relational datasets. Featuretools uses DFS for automated feature engineering. You can combine your raw data with what you know about your data to build meaningful features for machine learning and predictive modeling. Featuretools provides APIs to ensure only valid data is used for calculations, keeping your feature vectors safe from common label leakage problems. You...
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    gensim

    gensim

    Topic Modelling for Humans

    Gensim is a Python library for topic modeling, document indexing, and similarity retrieval with large corpora. The target audience is the natural language processing (NLP) and information retrieval (IR) community.
    Downloads: 0 This Week
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  • 6
    MagicTime

    MagicTime

    Time-lapse Video Generation Models as Metamorphic Simulators

    This repository is the official implementation of MagicTime, a metamorphic video generation pipeline based on the given prompts. The main idea is to enhance the capacity of video generation models to accurately depict the real world through our proposed methods and dataset. Compared to general videos, metamorphic videos contain physical knowledge, long persistence, and strong variation, making them difficult to generate.
    Downloads: 0 This Week
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  • 7
    Langcorn

    Langcorn

    Serving LangChain LLM apps automagically with FastApi

    LangCorn is an API server that enables you to serve LangChain models and pipelines with ease, leveraging the power of FastAPI for a robust and efficient experience.
    Downloads: 0 This Week
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  • 8
    Kor

    Kor

    LLM

    This is a half-baked prototype that “helps” you extract structured data from text using LLMs. Specify the schema of what should be extracted and provide some examples. Kor will generate a prompt, send it to the specified LLM and parse out the output. You might even get results back.
    Downloads: 0 This Week
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  • 9
    Guardrails

    Guardrails

    Adding guardrails to large language models

    Guardrails is a Python package that lets a user add structure, type and quality guarantees to the outputs of large language models (LLMs). At the heart of Guardrails is the rail spec. rail is intended to be a language-agnostic, human-readable format for specifying structure and type information, validators and corrective actions over LLM outputs. We create a RAIL spec to describe the expected structure and types of the LLM output, the quality criteria for the output to be considered valid...
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  • 10
    Bard API

    Bard API

    The unofficial python package that returns response of Google Bard

    The Python package returns a response of Google Bard through the value of the cookie. This package is designed for application to the Python package ExceptNotifier and Co-Coder. Please note that the bardapi is not a free service, but rather a tool provided to assist developers with testing certain functionalities due to the delayed development and release of Google Bard's API. It has been designed with a lightweight structure that can easily adapt to the emergence of an official API. Therefore...
    Downloads: 0 This Week
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  • 11
    OpenLLM

    OpenLLM

    Operating LLMs in production

    ..., CLI, our Python/Javascript client, or any HTTP client.
    Downloads: 0 This Week
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  • 12
    PandasAI

    PandasAI

    PandasAI is a Python library that integrates generative AI

    PandasAI is a Python library that adds Generative AI capabilities to pandas, the popular data analysis and manipulation tool. It is designed to be used in conjunction with pandas, and is not a replacement for it. PandasAI makes pandas (and all the most used data analyst libraries) conversational, allowing you to ask questions to your data in natural language. For example, you can ask PandasAI to find all the rows in a DataFrame where the value of a column is greater than 5, and it will return...
    Downloads: 0 This Week
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  • 13
    GeneralAI

    GeneralAI

    Large-scale Self-supervised Pre-training Across Tasks, Languages, etc.

    Fundamental research to develop new architectures for foundation models and AI, focusing on modeling generality and capability, as well as training stability and efficiency.
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  • 14
    x-unet

    x-unet

    Implementation of a U-net complete with efficient attention

    Implementation of a U-net complete with efficient attention as well as the latest research findings. For 3d (video or CT / MRI scans).
    Downloads: 0 This Week
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  • 15
    fastai

    fastai

    Deep learning library

    ... of many deep learning and data processing techniques in terms of decoupled abstractions. These abstractions can be expressed concisely and clearly by leveraging the dynamism of the underlying Python language and the flexibility of the PyTorch library. fastai is organized around two main design goals: to be approachable and rapidly productive, while also being deeply hackable and configurable. It is built on top of a hierarchy of lower-level APIs which provide composable building blocks.
    Downloads: 0 This Week
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  • 16
    Pyro

    Pyro

    Deep universal probabilistic programming with Python and PyTorch

    Pyro is a flexible, universal probabilistic programming language (PPL) built on PyTorch. It allows for expressive deep probabilistic modeling, combining the best of modern deep learning and Bayesian modeling. Pyro is centered on four main principles: Universal, Scalable, Minimal and Flexible. Pyro is universal in that it can represent any computable probability distribution. It scales easily to large datasets with minimal overhead, and has a small yet powerful core of composable...
    Downloads: 0 This Week
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  • 17
    EasyRL

    EasyRL

    Reinforcement learning (RL) tutorial series

    easy-rl is a beginner-friendly reinforcement learning (RL) tutorial series and framework developed by Datawhale China. It provides educational resources and implementations of various RL algorithms to help new researchers and practitioners learn RL concepts.
    Downloads: 1 This Week
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  • 18
    TorchRec

    TorchRec

    Pytorch domain library for recommendation systems

    TorchRec is a PyTorch domain library built to provide common sparsity & parallelism primitives needed for large-scale recommender systems (RecSys). It allows authors to train models with large embedding tables sharded across many GPUs. Parallelism primitives that enable easy authoring of large, performant multi-device/multi-node models using hybrid data-parallelism/model-parallelism. The TorchRec sharder can shard embedding tables with different sharding strategies including data-parallel,...
    Downloads: 0 This Week
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  • 19
    dm_control

    dm_control

    DeepMind's software stack for physics-based simulation

    DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo. DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo physics. The MuJoCo Python bindings support three different OpenGL rendering backends: EGL (headless, hardware-accelerated), GLFW (windowed, hardware-accelerated), and OSMesa (purely software-based). At least one of these three backends must be available in order render through...
    Downloads: 0 This Week
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  • 20
    Taipy

    Taipy

    Turns Data and AI algorithms into production-ready web applications

    From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability. Taipy enhances performance with caching control of graphical events, optimizing rendering by selectively updating graphical components only upon interaction. Effortlessly manage massive datasets with Taipy's built-in decimator for charts, intelligently reducing the number of data points to save time and memory without losing the essence of your data's shape....
    Downloads: 0 This Week
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  • 21
    segment-geospatial

    segment-geospatial

    A Python package for segmenting geospatial data with the SAM

    The segment-geospatial package draws its inspiration from segment-anything-eo repository authored by Aliaksandr Hancharenka. To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the segment-anything-py and segment-geospatial Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. I have...
    Downloads: 0 This Week
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  • 22
    EvaDB

    EvaDB

    Database system for building simpler and faster AI-powered application

    Over the last decade, AI models have radically changed the world of natural language processing and computer vision. They are accurate on various tasks ranging from question answering to object tracking in videos. To use an AI model, the user needs to program against multiple low-level libraries, like PyTorch, Hugging Face, Open AI, etc. This tedious process often leads to a complex AI app that glues together these libraries to accomplish the given task. This programming complexity prevents...
    Downloads: 0 This Week
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  • 23
    ChatGPT Academic

    ChatGPT Academic

    ChatGPT extension for scientific research work

    ChatGPT extension for scientific research work, specially optimized academic paper polishing experience, supports custom shortcut buttons, supports custom function plug-ins, supports markdown table display, double display of Tex formulas, complete code display function, new local Python/C++/Go project tree Analysis function/Project source code self-translation ability, newly added PDF and Word document batch summary function/PDF paper full-text translation function. All buttons are dynamically...
    Downloads: 0 This Week
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  • 24
    Kaleidoscope-SDK

    Kaleidoscope-SDK

    User toolkit for analyzing and interfacing with Large Language Models

    kaleidoscope-sdk is a Python module used to interact with large language models hosted via the Kaleidoscope service available at: https://github.com/VectorInstitute/kaleidoscope. It provides a simple interface to launch LLMs on an HPC cluster, asking them to perform basic features like text generation, but also retrieve intermediate information from inside the model, such as log probabilities and activations. Users must authenticate using their Vector Institute cluster credentials. This can...
    Downloads: 0 This Week
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  • 25
    ktrain

    ktrain

    ktrain is a Python library that makes deep learning AI more accessible

    ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines...
    Downloads: 0 This Week
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