LLaMA in R with Keras and TensorFlow
Implementation and walk-through of LLaMA, a Large Language Model, in R, with TensorFlow and Keras.
Tag: R
Deep Learning with R, 2nd Edition
Announcing the release of "Deep Learning with R, 2nd Edition," a book that shows you how to get started with deep learning in R.
Train in R, run on Android: Image segmentation with torch
We train a model for image segmentation in R, using torch together with luz, its high-level interface. We then JIT-trace the model on example input, s…
Please allow me to introduce myself: Torch for R
Today, we are excited to introduce torch, an R package that allows you to use PyTorch-like functionality natively from R. No Python installation is re…
Training ImageNet with R
This post explores how to train large datasets with TensorFlow and R. Specifically, we present how to download and repartition ImageNet, followed by t…
Deepfake detection challenge from R
A couple of months ago, Amazon, Facebook, Microsoft, and other contributors initiated a challenge consisting of telling apart real and AI-generated ("…
State-of-the-art NLP models from R
Nowadays, Microsoft, Google, Facebook, and OpenAI are sharing lots of state-of-the-art models in the field of Natural Language Processing. However, fe…
TensorFlow 2.0 is here – what changes for R users?
TensorFlow 2.0 was finally released last week. As R users we have two kinds of questions. First, will my keras code still run? And second, what is it …
BERT from R
A deep learning model - BERT from Google AI Research - has yielded state-of-the-art results in a wide variety of Natural Language Processing (NLP) tas…
So, how come we can use TensorFlow from R?
Have you ever wondered why you can call TensorFlow - mostly known as a Python framework - from R? If not - that's how it should be, as the R packages …
