Posts

Dynamic linear models with tfprobability

Previous posts featuring tfprobability - the R interface to TensorFlow Probabili...

Adding uncertainty estimates to Keras models with tfpro...

As of today, there is no mainstream road to obtaining uncertainty estimates from...

Hierarchical partial pooling, continued: Varying slopes...

This post builds on our recent introduction to multi-level modeling with tfproba...

Tadpoles on TensorFlow: Hierarchical partial pooling wi...

This post is a first introduction to MCMC modeling with tfprobability, the R int...

Introducing mall for R...and Python

We are proud to introduce the {mall} package. With {mall}, you can use a local ...

Introducing Keras 3 for R

We are thrilled to introduce {keras3}, the next version of the Keras R package. ...

News from the sparkly-verse

Highlights to the most recent updates to `sparklyr` and friends

Chat with AI in RStudio

Interact with Github Copilot and OpenAI's GPT (ChatGPT) models directly in RStud...

Hugging Face Integrations

Hugging Face rapidly became a very popular platform to build, share and collabor...

Understanding LoRA with a minimal example

LoRA (Low Rank Adaptation) is a new technique for fine-tuning deep learning mode...

What are Large Language Models? What are they not?

This is a high-level, introductory article about Large Language Models (LLMs), t...

GPT-2 from scratch with torch

Implementing a language model from scratch is, arguably, the best way to develop...

safetensors 0.1.0

Announcing safetensors, a new R package allowing for reading and writing files i...

torch 0.11.0

torch v0.11.0 is now on CRAN. This release features much-enhanced support for ex...

LLaMA in R with Keras and TensorFlow

Implementation and walk-through of LLaMA, a Large Language Model, in R, with Ten...

Group-equivariant neural networks with escnn

Escnn, built on PyTorch, is a library that, in the spirit of Geometric Deep Lear...

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