Recurrent neural networks (RNNs) have been a very popular predictive modelling choice for sequence based applications. Here we consider RNNs for time series forecasting. The proposed distinct ...
What Is An Encoder-Decoder Architecture? An encoder-decoder architecture is a powerful tool used in machine learning, specifically for tasks involving sequences like text or speech. It’s like a ...
The scaling rule of language models has produced success like never before. These huge language models have gotten novel emerging capabilities in addition to demonstrating tremendous superiority over ...
Modern large language models (LLMs) have excellent performance on code reading and generation tasks, allowing more people to enter the once-mysterious field of computer programming. Architecturally, ...
One of the most exciting capabilities of contemporary large language models (LLMs) is their impressive performance on code understanding and generation tasks, expanding access to the previously arcane ...
A PyTorch implementation of the hierarchical encoder-decoder architecture (HRED) introduced in Sordoni et al (2015). It is a hierarchical encoder-decoder architecture for modeling conversation triples ...
Hi @jhillhouse92, Glad you were able to get through compilation issues with original trace. Yes, using latest torch-neuron 1.7.1.* would be recommended here and should be compatible with Neuron ...
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