Model Architecture - Mixture of Experts (MoE) models activate only a fraction of their parameters during inference, leading to faster inference [1] - Mixtral 8x7B by MistralAI is a popular MoE-based Large Language Model (LLM) [1] - Llama 4 is another popular MoE-based LLM [1]

LLM Architectures - The report compares Transformer and Mixture of Experts (MoE) architectures in Large Language Models (LLMs) [1] - The report provides clear explanations and visuals to illustrate the differences between the two architectures [1] Focus - The report focuses on explaining Transformer and MoE architectures in LLMs [1]

RT Avi Chawla (@_avichawla)Containerized versions of 450+ MCP servers in a single repo!- No manual setup—just pull the image.- Safe to run in isolated containers, unlike scripts.- Auto-updated daily.Easiest and safest way to use MCP servers with Agents. https://t.co/0dQAn8WBd7 ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):Containerized versions of 450+ MCP servers in a single repo!- No manual setup—just pull the image.- Safe to run in isolated containers, unlike scripts.- Auto-updated daily.Easiest and safest way to use MCP servers with Agents. https://t.co/0dQAn8WBd7 ...

GitHub repo → https://t.co/Bsl7RYllmn ...

Containerized versions of 450+ MCP servers in a single repo!- No manual setup—just pull the image.- Safe to run in isolated containers, unlike scripts.- Auto-updated daily.Easiest and safest way to use MCP servers with Agents. https://t.co/0dQAn8WBd7 ...

A new ensemble technique that outperforms XGBoost, CatBoost, and LightGBM.Find the details in the explainer thread below: https://t.co/cgyg5Y4U2UAvi Chawla (@_avichawla):ML researchers just built a new ensemble technique.It even outperforms XGBoost, CatBoost, and LightGBM.Here's a complete breakdown (explained visually): ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):ML researchers just built a new ensemble technique.It even outperforms XGBoost, CatBoost, and LightGBM.Here's a complete breakdown (explained visually): ...

Here's the visual again for your reference:To recap, instead of training 32 (or K) separate MLPs, TabM uses one shared model and a lightweight adapter layer.Check this visual 👇 https://t.co/lF0yc2UjBb ...

ML researchers just built a new ensemble technique.It even outperforms XGBoost, CatBoost, and LightGBM.Here's a complete breakdown (explained visually): ...