Browsing: Transformers

print(“\n” + “=”*70 + “\n4. Variable-length packed batch — no padding waste\n” + “=”*70) seqlens = [37, 120, 8, 200] total = sum(seqlens) H, K =…

, I submitted my MS thesis on Emotion Recognition in Conversation (ERC). The model, EmoNet, achieved a Weighted F1 of 39.18 on EmoryNLP — competitive with the public PapersWithCode…

“Beauty will save the world”— Fyodor Dostoevsky A. Introduction did not emerge overnight. Today’s transformer-based systems can feel almost magical, capable of capturing context and even…

def build_model(attn_type: str = “mla”, max_loop_iters: int = 8) -> tuple: “””Build a small OpenMythos model. Two attention variants supported. MLA — Multi-Latent Attention (compressed KV…

Introduction (X-45) forecasting fundamentally changes whenever we try to predict a very rare event. We must fundamentally shift what we are modelling to focus on tail…

In this tutorial, we build and run a Colab workflow for Gemma 3 1B Instruct using Hugging Face Transformers and HF Token, in a practical, reproducible,…

Residual connections are one of the least questioned parts of modern Transformer design. In PreNorm architectures, each layer adds its output back into a running hidden…

Google DeepMind is expanding its biological toolkit beyond the world of protein folding. After the success of AlphaFold, the Google’s research team has introduced AlphaGenome. This…

forecasting errors are not caused by bad time-series models. They are caused by ignoring structure. SKUs do not behave independently. They interact through shared plants, product…

(NLP) revolutionized how we interact with technology. Do you remember when chatbots first appeared and sounded like robots? Thankfully, that’s in the past! Transformer models have…