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  2. llama.cpp - Wikipedia

    en.wikipedia.org/wiki/Llama.cpp

    llama.cpp is an open source software library that performs inference on various large language models such as Llama. [3] It is co-developed alongside the GGML project, a general-purpose tensor library. [4] Command-line tools are included with the library, [5] alongside a server with a simple web interface. [6] [7]

  3. OpenVINO - Wikipedia

    en.wikipedia.org/wiki/OpenVINO

    OpenVINO is an open-source software toolkit for optimizing and deploying deep learning models. It enables programmers to develop scalable and efficient AI solutions with relatively few lines of code. It supports several popular model formats [2] and categories, such as large language models, computer vision, and generative AI.

  4. Ironclad (software) - Wikipedia

    en.wikipedia.org/wiki/Ironclad_(software)

    Ironclad was founded in 2014 by Jason Boehmig, a former attorney at Fenwick & West, and Cai GoGwilt, a former software engineer at Palantir. [9] The company participated in the summer 2015 batch of startup accelerator Y Combinator who provided the seed funding, and it launched with 200 companies already using the product in beta.

  5. Open-source artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Open-source_artificial...

    Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [1]

  6. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    Software Creator Initial release Software license [a] Open source Platform Written in Interface OpenMP support OpenCL support CUDA support ROCm support [1] Automatic differentiation [2] Has pretrained models Recurrent nets Convolutional nets RBM/DBNs Parallel execution (multi node) Actively developed BigDL: Jason Dai (Intel) 2016 Apache 2.0 ...

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