Demonstrates, at very small scale, how a language model is trained (unigram language model).

Demonstrates, at very small scale, how a language model is trained (unigram language model).

Interactive Monte Carlo simulation of the VNAE framework. A visual playground to test how Theta and Beta parameters influence win rates in asymmetric systems.

Demonstrates, at very small scale, how a language model is trained (two-context model).

Demonstrates, at very small scale, how a language model is trained (bigram language model).

Demonstrates, at very small scale, how a language model is trained (bigram language model).

Demonstrates, at very small scale, how a language model is trained (two-context model).

Can a cellular neural network learn how to reliably express meaningful patterns? This is a toy model for a gene regulatory network for cell specification.

Demonstrates, at very small scale, how a language model is trained (three-context model with explicit transform stage).

🚀 Train a custom unigram model using simple and efficient methods, enabling easy adoption for natural language processing tasks.

🐾 Train AI with 300 diverse contexts about animals to enhance understanding and interaction in natural language processing applications.

🐾 Train bigram models of 200 animal names to enhance natural language processing tasks in generating relevant text efficiently.

🚂 Train a custom GPT model with 300 contexts to enhance your natural language processing tasks and improve interactive applications.

🚀 Train and fine-tune GPT models with 400-context support to enhance conversational capabilities and improve AI interactions.

🚀 Train a 200-bigram language model with ease, enhancing text generation tasks and improving natural language processing capabilities.

🐾 Train a model using 100 unigram animal names to enhance natural language processing projects with simple, effective training data.