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TL;DR: Large language models process text through tokenization, embeddings, transformers, and self-attention. They are trained through pre-training, fine-tuning, and alignment, the...
The basics of how LLMs work, from tokens and Transformers to prompting and RAG.Continue reading on Medium »
LM Studio has added Z.ai’s new GLM-5.3-Flash model to Bionic, its AI agent platform, bringing multimodal input, a 1 million-token context window, and significantly lower pricing th...
Large Language Models (LLMs) have transformed the way applications process and generate natural language. They are widely used in chatbots, search systems, coding assistants, docum...
Large language models can perform many tasks without any additional training. They can answer questions, summarize text, generate code, classify information, and interact with tool...
Даже идеальная модель с бесконечным объемом текста не восстановит ту часть смысла, которая никогда не была закодирована в языковой форме.Представьте фразу в рабочем чате: «он снова...
AI applications do not always need the same language model for every request. A simple factual question may only require a small, fast model, while a request involving multiple con...
Ollama pulls model weights, keeps an HTTP server on port 11434, and hands any client an OpenAI-shaped endpoint pointed at your own machine. Learn how to manage, configure, and opti...
Large Language Models can take several seconds, or sometimes much longer, to produce a complete response. In a traditional blocking application, the caller waits until the entire r...
Large Language Models (LLMs) are commonly accessed through cloud APIs provided by services such as OpenAI, Anthropic, or Google Gemini. However, there are many situations where dev...
Large Language Models (LLMs) naturally respond with free-form text. That’s great for a chat interface, but most applications need to feed the model’s answer into the rest of the sy...
Large language models are good at understanding natural language, but applications usually need information in a predictable form. A customer support application, for example, may...
Aleph Alpha has released Kolibri, a 78.1B-parameter English-German Mixture-of-Experts model that activates only 3.46B parameters per token. It has a 1M-token context and per-reques...
Z.ai has released GLM-5.3-Flash, the first natively multimodal model in the GLM-5 series — a 320B-total / 18B-active MoE with a 1,048,576-token context window, MIT-licensed weights...
How we taught small language models to call tools with GRPO, and why the strictest rule worked bestContinue reading on Medium »
LLMs in 7 Days · Season 1, Day 1: tokens, next-token prediction and temperature, with a game of “be the LLM” and a real terminal chatbot…Continue reading on Medium »
Ant Group and inclusionAI open-sourced Ling-3.0-flash-VL, a 124B MoE multimodal model with 5.5B active parameters. BF16 and FP8 weights arrived September 9 with a vision feedback l...
Large Language Models can now process hundreds of thousands, and sometimes even millions, of tokens.Continue reading on Medium »
Исследователи Stanford Hazy Research представили CLM-8B - Contrastive Language Model, открытую 8B-модель для быстрых решений внутри агентных систем. В отличие от обычной LLM, котор...
Open-source large language models are AI systems you can study, adapt, and use without being locked into one company’s platform or rules. In 2025, they’re giving rese...
Rhea Goel of Amazon on replacing a re-ranker with an LLM: natural language objectives, fine-tuning, DPO, hard and soft constraints, distillation and LLM judges.
Bilibili's Index LLM team released Index-Translate under Apache-2.0: 2B, 9B and 35B-A3B preview text models for 150 languages, plus dubbing, syllable-control and long-document vari...
You don’t need a billion-dollar AI lab to understand how large language models work. You can build a small one yourself — and learn why…Continue reading on Data Science Collective...
Choosing the right framework for your large language model application comes down to one question: what are you actually optimizing for?
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