Model Architecture - Explains Transformer vs Mixture of Experts (MoE) in LLMs with visuals [1] - Focuses on clearly explaining Mixture of Experts in LLMs [1]

LLM 技术 - Transformer 与 Mixture of Experts (MoE) 在 LLMs 中的对比分析 [1] - 行业关注 DS (数据科学), ML (机器学习), LLMs (大型语言模型), 和 RAGs (检索增强生成) 的教程和见解 [1] 社交媒体互动 - 鼓励用户分享信息 [1] - 行业专家 Avi Chawla 在社交媒体上分享相关内容 [1]

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 ...

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):A great tool to estimate how much VRAM your LLMs actually need.Alter the hardware config, quantization, etc., and get to know about:- Generation speed (tokens/sec)- Precise memory allocation- System throughput, etc.No more VRAM guessing! https://t.co/lZbIink12f ...

A great tool to estimate how much VRAM your LLMs actually need.Alter the hardware config, quantization, etc., and get to know about:- Generation speed (tokens/sec)- Precise memory allocation- System throughput, etc.No more VRAM guessing! https://t.co/lZbIink12f ...

So robot body process automation is literally if human had to do something you basically open some browser or whatever take some data put into some other system click some button and all that stuff. So it records that human clicks on that desktop and tries to keep repeating it. So you kind of like get that automated and the hard part that they had is you can't do robotic process for unstructured data because it's not fixed they change it.So anything will be very very brutal. The bet that we are taking is th ...

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):9 MCP projects for AI engineers (with code): ...

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):OpenAI meets MCP!Now you can add tools from any MCP server to your OpenAI LLM calls.Below, I integrated the @MindsDB MCP server, which lets you query 200+ data sources in plain English or SQL.Takes just 3-5 lines of code! https://t.co/uzbBEq61AD ...

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):Train AI models on data that does not even exist!SDV is an open-source framework that uses ML to learn patterns from your real data and generate tabular synthetic data at scale.Supports built-in anonymization, validation, and more. https://t.co/KyTZsaILvh ...