Basic Semantic Search with Cohere
In this tutorial, we cover using sentence embeddings for semantic search using Cohere in a Gradient Notebook
3 years ago
Articles
Autoencoders and Visual Similarity
In this followup article, we will be taking a look at another beneficial use of autoencoders. We explored how an autoencoder's encoder can be used as a feature extractor with the extracted features then compared using cosine similarity in order to find similar images.
3 years ago
Dense Passage Retrieval in Open-Domain Question Answering
In this article, we talk about what Dense Passage Retrieval is, how it works, and its uses. We also show how to implement it using the Simple Transformers python library in a Gradient Notebook.
3 years ago
Understanding ProGAN
In this article, we will see some GANs improvements over time, then we go through the revolutionary ProGAN paper to see how it works and understand it in depth.
3 years ago
Apply Model Interpretability Algorithms on CIFAR10 Dataset
In this tutorial, we show how to apply model interpretability algorithms from Captum on simple models. We demo building a basic model and use attribution algorithms such as Integrated Gradients, Saliency, DeepLift, and NoiseTunnel to attribute the image's label to the input pixels and visualize it.
3 years ago
Denoising Autoencoders
In this article we took a look at one of the uses of autoencoders: image denoising. In this tutorial, we show how an autoencoder's representation learning allows it to learn mappings efficient enough to fix incorrect pixels/datapoints.
3 years ago
Introduction to Natural Language Processing using NLTK
In this article, we'll go over how to set up NLTK in a paperspace gradient and utilize it to carry out a variety of NLP operations during the text processing stage. Then, we will create a Keras model with the help of some NLTK tools for sentiment analysis text classification.
3 years ago
Run the Stable Diffusion Web UI from Gradient Deployments part 2: Updating the Container to Access New Features
In this article, we look at the steps for creating and updating a container for the Stable Diffusion Web UI, detail how to deploy the Web UI with Gradient, and discuss the newer features from the Stable Diffusion Web UI that have been added to the application since our last update.
3 years ago
Generalist models on Paperspace: Images, text, audio and video combined
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.
By
Nick Ball
