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This repository contains the code for coding, pretraining, and finetuning a GPT-like LLM and is the official code repository for the book Build a Large Language Model (From Scratch). (If you downloaded the code bundle from the Manning website, please consider visiting the official code repository on GitHub at https://github.com/rasbt/LLMs-from-scratch.) In Build a Large Language Model (From Scratc
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Model Zoo A collection of standalone TensorFlow and PyTorch models in Jupyter Notebooks. Classifiers Perceptron [TensorFlow] [PyTorch] Logistic Regression [TensorFlow] [PyTorch] Softmax Regression (Multinomial Logistic Regression) [TensorFlow] [PyTorch] Multilayer Perceptron [TensorFlow] [PyTorch] Multilayer Perceptron with Dropout [TensorFlow] [PyTorch] Multilayer Perceptron with Batch Normalizat
That's an interesting question, and I try to answer this in a very general way. In essence, deep learning offers a set of techniques and algorithms that help us to parameterize deep neural network structures -- artificial neural networks with many hidden layers and parameters. One of the key ideas behind deep learning is to extract high level features from the given dataset. Thereby, deep learning
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