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  2. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    Typically, LLMs are trained with single- or half-precision floating point numbers (float32 and float16). One float16 has 16 bits, or 2 bytes, and so one billion parameters require 2 gigabytes. The largest models typically have 100 billion parameters, requiring 200 gigabytes to load, which places them outside the range of most consumer electronics.

  3. Language model - Wikipedia

    en.wikipedia.org/wiki/Language_model

    A language model is a model of natural language. [1] Language models are useful for a variety of tasks, including speech recognition [2], machine translation, [3] natural language generation (generating more human-like text), optical character recognition, route optimization, [4] handwriting recognition, [5] grammar induction, [6] and information retrieval.

  4. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    For example, a prompt may include a few examples for a model to learn from, such as asking the model to complete "maison → house, chat → cat, chien →" (the expected response being dog), [23] an approach called few-shot learning. [24] In-context learning is an emergent ability [25] of large language models.

  5. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.

  6. Few-shot learning - Wikipedia

    en.wikipedia.org/wiki/Few-shot_learning

    Few-shot learning and one-shot learning may refer to: Few-shot learning, a form of prompt engineering in generative AI; One-shot learning (computer vision)

  7. 3 places the Missouri football defense can improve on other ...

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  8. Transformer (deep learning architecture) - Wikipedia

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

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

  9. ‘Missouri is becoming a safer place.’ Third boarding school ...

    www.aol.com/missouri-becoming-safer-place-third...

    Smock came to Missouri from Arizona and in 2006 built an 11-bedroom mansion with an indoor pool and gymnasium on the property at 6360 E. 1570 Road, which he used as his home and business addresses.

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