Showing 5 open source projects for "data integration"

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  • 1
    Langflow

    Langflow

    Low-code app builder for RAG and multi-agent AI applications

    Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database.
    Downloads: 5 This Week
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    DomE

    DomE

    Implements a reference architecture for creating information systems

    ...With software engineering techniques, self-adaptive systems, and artificial intelligence, it is possible, the integration between design time and execution time.
    Downloads: 0 This Week
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  • 3
    GANformer

    GANformer

    Generative Adversarial Transformers

    This is an implementation of the GANformer model, a novel and efficient type of transformer, explored for the task of image generation. The network employs a bipartite structure that enables long-range interactions across the image, while maintaining computation of linearly efficiency, that can readily scale to high-resolution synthesis. The model iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of...
    Downloads: 0 This Week
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  • 4
    GPT Neo

    GPT Neo

    An implementation of model parallel GPT-2 and GPT-3-style models

    An implementation of model & data parallel GPT3-like models using the mesh-tensorflow library. If you're just here to play with our pre-trained models, we strongly recommend you try out the HuggingFace Transformer integration. Training and inference is officially supported on TPU and should work on GPU as well. This repository will be (mostly) archived as we move focus to our GPU-specific repo, GPT-NeoX.
    Downloads: 2 This Week
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  • 5
    Edward

    Edward

    A probabilistic programming language in TensorFlow

    ...Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilistic models, ranging from classical hierarchical models on small data sets to complex deep probabilistic models on large data sets. Edward fuses three fields, Bayesian statistics and machine learning, deep learning, and probabilistic programming. Edward is built on TensorFlow. It enables features such as computational graphs, distributed training, CPU/GPU integration, automatic differentiation, and visualization with TensorBoard. ...
    Downloads: 0 This Week
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