Models

This paper pursues the insight that giant language models (LLMs) trained to generate code can vastly improve the effectiveness of mutation operators applied to programs in genetic programming (GP). Because such LLMs profit from...

Codex, a big language model (LLM) trained on a wide range of codebases, exceeds the previous state-of-the-art in its capability to synthesize and generate code. Although Codex provides a plethora of advantages, models which...

We show that autoregressive language models can learn to infill text after we apply a simple transformation to the dataset, which simply moves a span of text from the center of a document to...

As generative language models improve, they open up recent possibilities in fields as diverse as healthcare, law, education and science. But, as with every recent technology, it's value considering how they will be misused....

Data drift occurs when the statistical properties of the input data change over time, resulting in a shift in the info distribution.Note:With default logic, z test is used for goal and KS test is...

Use natural language to check the behavior of your ML modelsImagine you create an ML model to predict customer sentiment based on reviews. Upon deploying it, you realize that the model incorrectly labels certain...

Cohere, OpenAI, and AI21 Labs have developed a preliminary set of best practices applicable to any organization developing or deploying large language models.

Construct and train a segmentation model with a couple of lines of codeThere are over 400 encoders, thus it’s impossible to point out all of them, but you'll find a comprehensive list here.Once the...