Showing 38 open source projects for "cpu-x"

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  • 1
    LocalGPT

    LocalGPT

    Chat with your documents on your local device using GPT models

    ...An independent verification pass is intended to improve answer reliability before results are returned. The platform works with Ollama models, offers a browser interface and API, and can run through local or Docker-based setups. It supports CPU and several hardware acceleration environments while retaining conversation history within a session.
    Downloads: 0 This Week
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  • 2
    Multimodal

    Multimodal

    TorchMultimodal is a PyTorch library

    ...The repository also includes example scripts and datasets for common multimodal tasks (e.g. retrieval, visual question answering, grounding) so you can test and compare models end to end. Installation supports both CPU and CUDA, and the codebase is versioned, tested, and maintained.
    Downloads: 0 This Week
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  • 3
    Free-AppleId-Serve

    Free-AppleId-Serve

    Shared account, Quantumult X, Circle x, stash, Little Rocket node

    Free AppleId Serve is a Chinese-language resource repository centered on shared foreign-region Apple IDs, proxy clients, and network subscription resources. It aggregates information for iOS tools such as Shadowrocket, Quantumult X, Stash, and related applications. The repository also maintains tutorials for proxy clients across iOS, macOS, Windows, and Android. A Python automation script collects publicly shared Apple account credentials from several external providers and updates repository content. Additional sections catalog free proxy subscriptions and services using technologies such as Clash, V2Ray, Shadowsocks, and Trojan. ...
    Downloads: 2 This Week
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  • 4
    AIMET

    AIMET

    AIMET is a library that provides advanced quantization and compression

    ...Quantized inference is significantly faster than floating point inference. For example, models that we’ve run on the Qualcomm® Hexagon™ DSP rather than on the Qualcomm® Kryo™ CPU have resulted in a 5x to 15x speedup. Plus, an 8-bit model also has a 4x smaller memory footprint relative to a 32-bit model. However, often when quantizing a machine learning model (e.g., from 32-bit floating point to an 8-bit fixed point value), the model accuracy is sacrificed.
    Downloads: 32 This Week
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  • 5
    DocTR

    DocTR

    Library for OCR-related tasks powered by Deep Learning

    DocTR provides an easy and powerful way to extract valuable information from your documents. Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document...
    Downloads: 12 This Week
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  • 6
    FairChem

    FairChem

    FAIR Chemistry's library of machine learning methods for chemistry

    ...Tasks span heterogeneous domains—catalysis (OC20-style), inorganic materials (OMat), molecules (OMol), MOFs (ODAC), and molecular crystals (OMC)—allowing one model family to serve many simulations. The README provides quick paths for pulling models (e.g., via Hugging Face access), then running energy/force predictions on GPU or CPU.
    Downloads: 0 This Week
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  • 7
    PennyLane

    PennyLane

    A cross-platform Python library for differentiable programming

    ...Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy, PyTorch, JAX, or TensorFlow, allowing hybrid CPU-GPU-QPU computations. The same quantum circuit model can be run on different devices. Install plugins to run your computational circuits on more devices, including Strawberry Fields, Amazon Braket, Qiskit and IBM Q, Google Cirq, Rigetti Forest, and the Microsoft QDK.
    Downloads: 13 This Week
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  • 8
    parallel-ssh

    parallel-ssh

    Asynchronous parallel SSH client library.

    parallel-ssh is an asynchronous parallel SSH library designed for large-scale automation. It differentiates itself from alternatives, other libraries and higher-level frameworks like Ansible or Chef in several ways.
    Downloads: 0 This Week
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  • 9
    Jupyter Docker Stacks

    Jupyter Docker Stacks

    Ready-to-run Docker images containing Jupyter applications

    Jupyter Docker Stacks provides a curated set of ready-to-run Docker container images that bundle Jupyter applications with popular data science and computing tools, enabling users to quickly start working in a reproducible environment. These stacks support a range of use cases, from lightweight base notebook images to full featured environments that include scientific computing libraries, machine learning tools, and IDE-like notebook interfaces, all within Docker containers that run...
    Downloads: 1 This Week
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  • 10
    Python colorlog

    Python colorlog

    A colored formatter for the python logging module

    Add colors to the output of Python's logging module. This library is over a decade old and supported a wide set of Python versions for most of its life, which has made it a difficult library to add new features to. colorlog 6 may break backward compatibility so that newer features can be added more easily, but may still not accept all changes or feature requests. colorlog 4 might accept essential bug fixes but should not be considered actively maintained and will not accept any major changes...
    Downloads: 0 This Week
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  • 11
    PyTensor

    PyTensor

    Python library for defining and optimizing mathematical expressions

    PyTensor is a fork of Aesara, a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays. PyTensor is based on Theano, which has been powering large-scale computationally intensive scientific investigations since 2007. A hackable, pure-Python codebase. Extensible graph framework is suitable for rapid development of custom operators and symbolic optimizations. Implements an extensible graph transpilation framework that...
    Downloads: 0 This Week
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  • 12
    RLax

    RLax

    Library of JAX-based building blocks for reinforcement learning agents

    ...It supports both on-policy and off-policy learning, as well as value-based, policy-based, and model-based approaches. RLax is fully JIT-compilable with JAX, enabling high-performance execution across CPU, GPU, and TPU backends. The library implements tools for Bellman equations, return distributions, general value functions, and policy optimization in both continuous and discrete action spaces. It integrates seamlessly with DeepMind’s Haiku (for neural network definition) and Optax (for optimization), making it a key component in modular RL pipelines.
    Downloads: 0 This Week
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  • 13
    Face Alignment

    Face Alignment

    2D and 3D Face alignment library build using pytorch

    Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively...
    Downloads: 0 This Week
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  • 14
    PyTorch Geometric

    PyTorch Geometric

    Geometric deep learning extension library for PyTorch

    ...In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations.
    Downloads: 0 This Week
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  • 15
    go1pylib

    go1pylib

    go1pylib is a Python library designed to control the Go1 robot

    go1pylib is a Python library designed to control the Go1 robot by Unitree Robotics. It provides an easy-to-use interface for robot movement, state management, collision avoidance, battery monitoring, and MQTT communication. Ideal for research and robotics development.
    Downloads: 0 This Week
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  • 16
    The Reactive Extensions for Python

    The Reactive Extensions for Python

    Reactive extensions for Python

    RxPY is a library for composing asynchronous and event-based programs using observable collections and pipable query operators in Python. A library for composing asynchronous and event-based programs using observable collections and query operator functions in Python. Reactive Extensions for Python (RxPY) is a set of libraries for composing asynchronous and event-based programs using observable sequences and pipable query operators in Python. Using Rx, developers represent asynchronous data...
    Downloads: 0 This Week
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  • 17
    DGL

    DGL

    Python package built to ease deep learning on graph

    ...We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. DGL provides a powerful graph object that can reside on either CPU or GPU. It bundles structural data as well as features for a better control. We provide a variety of functions for computing with graph objects including efficient and customizable message passing primitives for Graph Neural Networks.
    Downloads: 1 This Week
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  • 18
    Shumai

    Shumai

    Fast Differentiable Tensor Library in JavaScript & TypeScript with Bun

    ...The library supports matrix operations, gradient computation, and tensor conversions with intuitive APIs and near-native speed, thanks to Bun’s low-overhead FFI bindings. It can automatically leverage GPU acceleration on Linux (via CUDA) and CPU computation on macOS.
    Downloads: 0 This Week
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  • 19
    lixa

    lixa

    LIXA, LIbre XA, is a free and open source XA transaction manager

    LIXA (LIbre XA) is an open source and free Transaction Manager implementing the distributed transaction processing "XA specification" and "TX (transaction demarcation) specification" according to the X/Open CAE Specification. LIXA implements even XTA: XA Transaction API, an innovative API that implements XA transactional context passing among different applications. LIXA is a Transaction Manager but it's not a Transaction Monitor: this is the distinguishing feature of the project. LIXA technology enables every application container, like a web server or a shell, to become a two phase commit application server. ...
    Downloads: 0 This Week
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  • 20
    Neural Tangents

    Neural Tangents

    Fast and Easy Infinite Neural Networks in Python

    Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels,...
    Downloads: 0 This Week
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  • 21
    flom

    flom

    Free Lock Manager

    ...libflom, the library shipped with FLoM, allows you to develop your own application using a simple C, C++, Java, Perl, PHP or Python client API. SSL/TLS security for network communication, X.509 certificates for peer to peer mutual authentication.
    Downloads: 0 This Week
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  • 22
    Fairseq

    Fairseq

    Facebook AI Research Sequence-to-Sequence Toolkit written in Python

    Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the...
    Downloads: 0 This Week
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  • 23
    blind-watermark

    blind-watermark

    Blind&Invisible Watermark, image blind watermark, extract watermark

    ...The package provides both a Python API and command-line interface for embedding and extraction. Its examples evaluate recovery after rotation, cropping, masking, resizing, noise, cuts, and brightness changes. Multiprocessing can use several CPU cores during processing. The project is intended for copyright marking, traceability, and image steganography experiments.
    Downloads: 2 This Week
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  • 24
    TRFL

    TRFL

    TensorFlow Reinforcement Learning

    ...The library is designed to integrate seamlessly with TensorFlow, allowing users to define differentiable RL objectives and train models using standard optimization routines. TRFL supports both CPU and GPU TensorFlow environments, though TensorFlow itself must be installed separately. It exposes clean, modular APIs for various RL methods including Q-learning, policy gradient, and actor-critic algorithms, among others. Each function returns not only the computed loss tensor but also a detailed structure containing auxiliary information like TD errors and targets.
    Downloads: 0 This Week
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  • 25
    TFLearn

    TFLearn

    Deep learning library featuring a higher-level API for TensorFlow

    ...Powerful helper functions to train any TensorFlow graph, with support of multiple inputs, outputs, and optimizers. Easy and beautiful graph visualization, with details about weights, gradients, activations, and more. Effortless device placement for using multiple CPU/GPU. The high-level API currently supports the most of the recent deep learning models, such as Convolutions, LSTM, BiRNN, BatchNorm, etc.
    Downloads: 0 This Week
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