Showing 6 open source projects for "programming without coding"

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  • 1
    CodeGeeX

    CodeGeeX

    CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)

    CodeGeeX is a large-scale multilingual code generation model with 13 billion parameters, trained on 850B tokens across more than 20 programming languages. Developed with MindSpore and later made PyTorch-compatible, it is capable of multilingual code generation, cross-lingual code translation, code completion, summarization, and explanation. It has been benchmarked on HumanEval-X, a multilingual program synthesis benchmark introduced alongside the model, and achieves state-of-the-art performance...
    Downloads: 7 This Week
    Last Update:
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  • 2
    cuML

    cuML

    RAPIDS Machine Learning Library

    cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU...
    Downloads: 0 This Week
    Last Update:
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  • 3
    CodeContests

    CodeContests

    Large dataset of coding contests designed for AI and ML model training

    CodeContests, developed by Google DeepMind, is a large-scale competitive programming dataset designed for training and evaluating machine learning models on code generation and problem solving. This dataset played a central role in the development of AlphaCode, DeepMind’s model for solving programming problems at a human-competitive level, as published in Science. CodeContests aggregates problems and human-written solutions from multiple programming competition platforms, including AtCoder...
    Downloads: 0 This Week
    Last Update:
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  • 4
    Caffe Framework

    Caffe Framework

    Caffe, a fast open framework for deep learning

    Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine...
    Downloads: 1 This Week
    Last Update:
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  • 5
    Simdist lets you harness the power of cluster computing without any knowledge of parallel libraries such as MPI, and with no restrictions on programming language. Primarily targeted at evolutionary computing and similar master-slave configurations.
    Downloads: 0 This Week
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  • 6
    Morasot SimSoccer Team is a proposed team for RoboSoccer simulator v 1.4. The team consists in 5 simulated players (given as a win32 dll). Several coding techiques are shown for efficient soccer playing using object-oriented programming (SimuroSot league
    Downloads: 0 This Week
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