Dr. Nick Ball is a generalist data scientist who joined Paperspace in November 2020. He has been using machine learning since 2000, first in academia (astrophysics), then in Silicon Valley since 2013.
Improve your images versus raw Stable Diffusion with no extra work needed from the user: by adding self-attention guidance, images generated from text prompts are more realistic and nicer to look at.
We're excited to launch "pay-as-you-grow" access to Graphcore IPUs.
A new class of deep learning called a generalist model is capable of running on images, text, audio, video and more all at the same time. Here we explore the capabilities of 3 of these models: Perceiver IO, Data2vec, and Gato. We show how to run Perceiver IO on Paperspace.
In this article, we discuss the process of conducting end-to-end data science on Gradient with Nvidia Merlin. This includes walkthroughs on 3 examples: Multi-stage recommenders, training and serving a MovieLens model, and scaling for the massive Criteo dataset.
In this blogpost, we discuss the benefits and utilities of using PyTorch Lightning with Gradient Notebooks to optimize and simplify deep learning code, as well as extend the capabilities of Torch beyond the scope of the original package.
In this article, we examine HuggingFace's Accelerate library for multi-GPU deep learning. We apply Accelerate with PyTorch and show how it can be used to simplify transforming raw PyTorch into code that can be run on a distributed machine system.
In this post, readers will see how to implement a decision transformer with OpenAI Gym on a Gradient Notebook to train a hopper-v3 "robot" to hop forward over a horizontal boundary as quickly as possible.
Follow this guide to learn how to set up and use GPT-NeoX-20B within Paperspace Gradient to generate text in response to an inputted prompt.
Follow this guide to see how to run distributed training with TensorFlow on Gradient Multi-GPU powered instances!
