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jaykmody.com | ||
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amatria.in
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| | | | | [AI summary] The provided text is an extensive overview of various large language models (LLMs) and their architectures, training tasks, and applications. It includes detailed descriptions of models like GPT, T5, BERT, and others, along with their pre-training objectives, parameter counts, and specific use cases. The text also references key research papers, surveys, and resources for further reading on LLMs and related topics. | |
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zserge.com
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| | | | | Finally, building a simple GPT model that would finish our sentences. | |
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explainextended.com
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| | | | | A complete GPT2 implementation as a single SQL query in PostgreSQL. | |
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neuralnetworksanddeeplearning.com
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| | | [AI summary] The text provides an in-depth explanation of the backpropagation algorithm in neural networks. It starts by discussing the concept of how small changes in weights propagate through the network to affect the final cost, leading to the derivation of the partial derivatives required for gradient descent. The explanation includes a heuristic argument based on tracking the perturbation of weights through the network, resulting in a chain of partial derivatives. The text also touches on the historical context of how backpropagation was discovered, emphasizing the process of simplifying complex proofs and the role of using weighted inputs (z-values) as intermediate variables to streamline the derivation. Finally, it concludes with a citation and licens... | ||
