We'll be using json-server to create the REST API that we'll fetch data from. In the root of the project, create a db.json file with the contents. - Source: dev.to / 17 days ago

Our backend will be little more than a two-way translation layer between the database and the user interface (UI). Later in this post we will identify other responsibilities of a backend but our implementation will be kept simple to demonstrate the fundamental machinery and concepts. It is worth noting the backend comes in two parts, web server and application server. Both json-server and Express are able to... - Source: dev.to / 12 months ago

JSON-Server creates fake REST API with a minimum amount of configuration, it provides a simple way to create mock RESTful APIs and easily define the required endpoints, allows easy definition of the data schema in a JSON file and can serve as a reference for each figure in the project. - Source: dev.to / about 1 year ago

I thought about usingJson Server (hosting the repo with the words on Github to begin with), Googlesheets, or maybe Firestore (i would prefer not to use it ,to avoid extra costs just in case it gets a reasonable amount of users). It isnt a big app so I just want a simple solution for storing the words and fetching them. Source: about 1 year ago

First, I didn't create a backend API for this example, but I used a fake API to test. I created it with json-server and json-server-auth. They are two npm packages that use a JSON file as a database and expose the database in an API. You can find more about json-server in its documentation and about json-server-auth here. - Source: dev.to / over 1 year ago

Many settings affect the outputs in interesting ways, but that's half the fun. These LoRAs are very lightly trained; more training may or may not help. The competitions are also performed using zero-shot text guessing, and if Facebook said it, you can bet that's actually Meta AI saying it, and they are leaders in the field. Source: over 1 year ago

You should look at the entire niche of MAE-related papers, that's quite exciting, and the neuroscience-inspired stream of stuff like Barlow Twins. As well, the official Facebook AI blog is surprisingly good coverage of much of the interesting un/semi-supervised DL research FAIR does, and worth going through. Source: almost 2 years ago