Showing 36 open source projects for "default software"

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  • 1
    HyperGAN

    HyperGAN

    Composable GAN framework with api and user interface

    A composable GAN built for developers, researchers, and artists. HyperGAN builds generative adversarial networks in PyTorch and makes them easy to train and share. HyperGAN is currently in pre-release and open beta. Everyone will have different goals when using hypergan. HyperGAN is currently beta. We are still searching for a default cross-data-set configuration. Each of the examples supports search. Automated search can help find good configurations. If you are unsure, you can start with...
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  • 2
    captcha_break

    captcha_break

    Identification codes

    This project will use Keras to build a deep convolutional neural network to identify the captcha verification code. It is recommended to use a graphics card to run the project. The following visualization codes are jupyter notebookall done in . If you want to write a python script, you can run it normally with a little modification. Of course, you can also remove these visualization codes. captcha is a library written in python to generate verification codes. It supports image verification...
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  • 3
    H.B.S.N

    H.B.S.N

    Speech Recognition System

    H.B.S.N is a simple speech recognition software which programmed using Java. This software is a package of many sub applications.And those are as listed below , Audio Player Video Player Email Client Weather Application Mp3 Tag Editor Picture Viewer Home Automation Application Alarm / Timer Folder Locker Message Encrypt Application Income & Expenses Logging Application Apart from that we can do many thing from this software by using voice commands , such as , Open & close applications which are installed in the computer Open web sites Open folders which are in the HDD Control built-in audio & video player Control the home automation system Reading mails Reading selected text Speaking clock ( Time & Date) Speaking weather report There are system commands for the tasks which this application does.And we can replace the system default commands with custom commands.
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  • 4
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu...
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  • 5
    MDictate

    MDictate

    Speech to text using python, pocketsphinx, ready to deploy

    Automated speech recognition software is extremely cumbersome. This project's aim is to incrementally improve the quality of an open-source and ready to deploy speech to text recognition system. Runs on Windows using the mdictate.exe, but the core workings are found in the mdictate.py script which should work on Windows/Linux/OS X. In version 1.0, we use pocketsphinx' default setup with a basic graphic interface.
    Downloads: 1 This Week
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  • 6
    S-Match

    S-Match

    S-Match is a semantic matching framework.

    S-Match is a semantic matching framework. S-Match takes any two tree like structures (such as database schemas, classifications, lightweight ontologies) and returns a set of correspondences between those tree nodes which semantically correspond to one another. S-Match contains implementations of the semantic matching, minimal semantic matching and structure preserving semantic matching algorithms. S-Match applies as a solution in many fields, including: information integration,...
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  • 7

    NeuroSolutions: Formula Generator

    Utility converts the weights file of a MLP Breadboard into a formula

    The NeuroSolutions: Formula Generator utility converts the weights file of a default MLP breadboard (1-hidden layer with a TanhAxon in the hidden layer and either a TanhAxon or BiasAxon in the output layer) into a usable formula that can be copied and pasted into your own programs to compute the output of the trained neural network.
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  • 8

    drvq

    dimensionality-recursive vector quantization

    ...As a by-product of training, a tree structure performs either exact or approximate quantization on trained centroids, the latter being not very precise but extremely fast. A detailed README file describes the usage of the software, including license, requirements, installation, file formats, sample data, tools, and options. With the sample data provided and the default options, it is possible to test the code immediately as a demo. DRVQ has a 2-clause BSD license. Please refer to the DRVQ software home page, the research project, or the original publication for more information. ...
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  • 9
    TextBlob

    TextBlob

    TextBlob is a Python library for processing textual data

    Simple, Pythonic, text processing, Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more. TextBlob stands on the giant shoulders of NLTK and pattern, and plays nicely with both. Supports word inflection (pluralization and singularization) and lemmatization,...
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  • 10
    Ornith-1.0

    Ornith-1.0

    Open reasoning model for agentic coding and tool workflows

    ...Ornith-1.0-397B is a reasoning model by default, generating <think> blocks before final answers, and supports tool calling through OpenAI-compatible endpoints. It can be deployed with vLLM, SGLang, Transformers, Docker, and compatible quantized local apps, and is released under the MIT license.
    Downloads: 0 This Week
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  • 11
    Kimi K2.7 Code

    Kimi K2.7 Code

    Coding-focused Kimi model for long-horizon agent workflows

    ...The model supports image and video input, native INT4 quantization, interleaved thinking, and multi-step tool calling. It also forces preserve-thinking mode by default, retaining full reasoning context across multi-turn interactions to improve coding-agent consistency. K2.7 Code is recommended for use through Kimi Code CLI and can be deployed with vLLM, SGLang, or KTransformers.
    Downloads: 0 This Week
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