LLMs
In the evolving landscape of open-source language models, SmolLM3 emerges as a breakthrough: a 3 billion-parameter, decoder-only transformer that rivals larger 4 billion-parameter peers on many benchmarks, while natively supporting
Developing intelligent agents, using LLMs like GPT-4o, Gemini, etc., that can perform tasks requiring multiple steps, adapt to changing information, and make decisions is a core challenge in AI development.
SigLIP-2 represents a significant step forward in the development of multilingual vision-language encoders, bringing enhanced semantic understanding, localization, and dense feature extraction capabilities. Built on the foundations of SigLIP, this
Unsloth has emerged as a game-changer in the world of large language model (LLM) fine-tuning, addressing what has long been a resource-intensive and technically complex challenge. Adapting models like LLaMA,