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  2. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    The safetensors format was developed around 2021 to solve problems with using Python's pickle format (that was then used in PyTorch). It was designed for saving and loading tensors. Compared to pickle format, it allows lazy loading, and avoids security problems. [21] After a security audit, it became the default format in 2023. [22]

  3. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    The transformer model has been implemented in standard deep learning frameworks such as TensorFlow and PyTorch. Transformers is a library produced by Hugging Face that supplies transformer-based architectures and pretrained models.

  4. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    In September 2022, Meta announced that PyTorch would be governed by the independent PyTorch Foundation, a newly created subsidiary of the Linux Foundation. [ 24 ] PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo , a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and ...

  5. llama.cpp - Wikipedia

    en.wikipedia.org/wiki/Llama.cpp

    The GGUF (GGML Universal File) [30] file format is a binary format that stores both tensors and metadata in a single file, and is designed for fast saving, and loading of model data. [31] It was introduced in August 2023 by the llama.cpp project to better maintain backwards compatibility as support was added for other model architectures.

  6. Torch (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Torch_(machine_learning)

    The torch package also simplifies object-oriented programming and serialization by providing various convenience functions which are used throughout its packages. The torch.class(classname, parentclass) function can be used to create object factories ().

  7. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    The fixed back-connections save a copy of the previous values of the hidden units in the context units (since they propagate over the connections before the learning rule is applied). Thus the network can maintain a sort of state, allowing it to perform tasks such as sequence-prediction that are beyond the power of a standard multilayer ...

  8. Medical open network for AI - Wikipedia

    en.wikipedia.org/wiki/Medical_open_network_for_AI

    The distributed data-parallel APIs seamlessly integrate with the native PyTorch distributed module, PyTorch-ignite [21] distributed module, Horovod, XLA, [22] and the SLURM platform. [ 23 ] DL model collection: by offering the MONAI Model Zoo, [ 24 ] MONAI establishes itself as a platform that enables researchers and data scientists to access ...

  9. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    [33] [43] In addition to building and training their model, TensorFlow can also help load the data to train the model, and deploy it using TensorFlow Serving. [ 44 ] TensorFlow provides a stable Python Application Program Interface ( API ), [ 45 ] as well as APIs without backwards compatibility guarantee for Javascript , [ 46 ] C++ , [ 47 ] and ...