Search Results for "self-extracing"

...The codebase is focused on local inference and generation through the Vortex inference stack rather than serving as a full training framework alone, although it also points users to training and fine-tuning resources. It supports multiple ways of working with the model, including forward passes, embeddings, generation workflows, notebooks, hosted APIs, and self-hosted deployment through NVIDIA NIM.

This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3...

LGTmate is a simple and powerful bioinformatic software tool to identify lateral gene transfer events and contaminants in Eukaryotic proteomes. It is available as a GUI or command-line application, with no dependencies and no installation required.

ProtPOS is a self-contained, lightweight, and easy-to-use software package for predicting the preferred orientation of protein on a given surface upon initial adsorption. It searches quickly for the low energy protein poses in all translational and rotational degrees of freedom of the protein with respect to the surface using particle swarm optimization.

Phobos is to be used for recording rodents' behavior during the thigmotaxis (open-field) and the elevated plus-maze tests. Phobos provides the possibility to easily calculate all possible experimental parameters at once immediately after the evaluation of the fear/anxiety level of each animal. All extracted files can be readily combined to one in order for statistical analyses to be performed. If you use Phobos for your research, please cite: Telonis AG, Margarity M.Phobos: a novel...

ArrayOligoSelector (AOS) systematically designs gene specific long oligo probes for entire genomes. The program optimizes the oligo selections for several parameters, including uniqueness in the genome, internal repeats, self-binding, and GC content.