CALM: Conditional Adversarial Latent Models for Directable Virtual Characters. Skills: CALM builds upon, and borrows code from, Adversarial Skill Embeddings.

This repository encapsulates all code required to reproduce the results of the paper "Codon language embeddings provide strong signals for use in protein ...

This is an implementation of language model inference, aiming to get maximum single-GPU single-batch hardware utilization for LLM architectures.

A fully runnable web app written in Java, it supports analysis by Static (SAST), Dynamic (DAST), and Runtime (IAST) tools that support Java.

This repository provides the code for implementing the CALM (Composition to Augment Language Models) framework described in the paper "LLMs Augmented LLMs: ...

Implementation of CALM from the paper "LLM Augmented LLMs: Expanding Capabilities through Composition", out of Google Deepmind - lucidrains/CALM-pytorch.

Generating Dataset. Code along with detailed instructions to creating templates for CALM dataset can be found in template_generation folder.

If you want to know how to install and run image analysis software on OnDemand, you've come to the right place. See below for instructions for specific ...

In this work, we present Conditional Adversarial Latent Models (CALM), an approach for generating diverse and directable behaviors for user-controlled ...

Nutanix Calm Blueprints. Contribute to nutanix/blueprints development by creating an account on GitHub.