Transformer architecture

Microsoft’s Inference Framework Brings 1-Bit Large Language Models to Local Devices

On October 17, 2024, Microsoft announced BitNet.cpp, an inference framework designed to run 1-bit quantized Large Language Models (LLMs). BitNet.cpp is a big progress in Gen AI, enabling the deployment of 1-bit LLMs efficiently...

The Most Powerful Open Source LLM Yet: Meta LLAMA 3.1-405B

Memory Requirements for Llama 3.1-405BRunning Llama 3.1-405B requires substantial memory and computational resources:GPU Memory: The 405B model can utilize as much as 80GB of GPU memory per A100 GPU for efficient inference. Using Tensor...

Understanding Large Language Model Parameters and Memory Requirements: A Deep Dive

Large Language Models (LLMs) has seen remarkable advancements in recent times. Models like GPT-4, Google's Gemini, and Claude 3 are setting latest standards in capabilities and applications. These models are usually not only enhancing...

Understanding Sparse Autoencoders, GPT-4 & Claude 3 : An In-Depth Technical Exploration

Introduction to AutoencodersPhoto: Michela Massi via Wikimedia Commons,(https://commons.wikimedia.org/wiki/File:Autoencoder_schema.png)Autoencoders are a category of neural networks that aim to learn efficient representations of input data by encoding after which reconstructing it. They comprise two foremost parts:...

A latest solution to let AI chatbots converse all day without crashing

When a human-AI conversation involves many rounds of continuous dialogue, the powerful...

Learning to grow machine-learning models

It’s no secret that OpenAI’s ChatGPT has some incredible capabilities — as...

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