Qwen

Large neural network models, with their extraordinary abilities, are firmly rooted in our lives. Recognizing this as an opportunity for future development, large corporations began to develop their own versions of these models. The Chinese giant, Alibaba, didn’t stand by. They created their own model, QWen (Tongyi Qianwen), which became the basis for many other neural network models. Prerequisites Update cache and packages Let’s update the packa

Large Language Models (LLMs) have significantly impacted our lives. Despite understanding their internal structure, these models remain a focal point for scientists who often liken them to a “black box”. The final result depends not only on the LLM’s design but also on its training and the data used for training. While scientists find research opportunities, end-users are primarily interested in two things: speed and quality. These criteria play a crucial role in t

The global AI race is accelerating. Research institutions, private corporations, and even entire nations are now competing for leadership in the AI domain. Broadly speaking, this race can be divided into several phases. The first stage involved the creation of narrow AI. Existing neural network models such as GPT, MidJourney, and AlphaFold show that this stage has been successfully achieved. The next step envisions the evolution of AI into AGI (Artificial General I

We’re used to thinking that open-source models always lag behind their commercial counterparts in quality. It may seem that they’re developed exclusively by enthusiasts who cannot afford to invest vast sums in creating high-quality datasets and training models on tens of thousands of modern GPUs. It’s a different story when large corporations like OpenAI, Anthropic, or Meta take on the task. They not only have the resources but also the world’s top neural network s