Stealing Part of a Production Language Model
What if we could discover OpenAI models internal weights? In this post we dive into a paper which presents an attack that steals LLMs data.
How Meta AI ‘s Human-Like V-JEPA Works?
Explore V-JEPA, which stands for Video Joint-Embedding Predicting Architecture. Another step in Meta AI’s journey for human-like AI
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
In this post we dive into the era of 1-bit LLMs paper by Microsoft, which shows a promising direction for low cost large language models
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Self-Rewarding Language Models by Meta AI
In this post we dive into the Self-Rewarding Language Models paper by Meta AI, which can possibly be a step towards open-source AGI
Fast Inference of Mixture-of-Experts Language Models with Offloading
Diving into a research paper introducing an innovative method to enhance LLM inference efficiency using memory offloading
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TinyGPT-V: Efficient Multimodal Large Language Model via Small Backbones
In this post we dive into TinyGPT-V, a small but mighty Multimodal LLM which brings Phi-2 success to vision-language tasks
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LLM in a flash: Efficient Large Language Model Inference with Limited Memory
In this post we dive into LLM in a flash paper by Apple, that introduces a method to run LLMs on devices that have limited memory
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Vision Transformers Explained | The ViT Paper
In this post we go back to the important vision transformers paper, to understand how ViT adapted transformers to computer vision
Orca 2: Teaching Small Language Models How to Reason
Dive into Orca 2 research paper, the second version of the successful Orca small language model from Microsoft,
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From Diffusion Models to LCM-LoRA
Following LCM-LoRA release, in this post we explore the evolution of diffusion models up to latent consistency models with LoRA