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Large language models (LLMs) are AI systems offered by LLM providers that process vast amounts of data to generate humanlike responses to natural language inputs. They are foundati...
Here are 5 small language models that hare one important trait: they all support structured tool calling in a compact, open-weight package.
Here are 5 small language models that hare one important trait: they all support structured tool calling in a compact, open-weight package.
Merge LLMs easily with Unsloth Studio's no-code GUI and combine models without retraining.
From tokenisation to evaluation — how modern language models actually work in practiceContinue reading on Towards AI »
In this article, we will go deep under the hood of Ollama's configuration engine, exploring how to fine-tune local language model parameters.
Hierarchical Pattern Learning for Hallucination-Free Text GenerationContinue reading on Medium »
Most people today are just calling APIs to use LLMs…Continue reading on Medium »
These ares seven unconventional uses of LLMs that go far beyond usual chat interface and conversations.
Post-training methods (RLVR, On-policy distillation) are Episode-local Language models are getting better at learning from feedback during post-training. In reinforcement learning...
IDI / Mental Model || What is it? Each person has their own mental model that represents the way they think, feel and/or behave in regards to everything. They are based on beli...
From tokenisation to evaluation :  how modern language models actually work in practice The post The Must-Know Topics for an LLM Engineer appeared first on Towards Data Scien...
Until recently, many people viewed large language models (LLMs) largely as toys interesting to look at but not very practical in a business setting. However, that perception has be...
When we need an LLM to perform a complex task, we often need to feed it a lot of context. Coming up with a design for a new feature requires descriptions of how we want the fea...
Most RAG tutorials focus on retrieval or prompting. The real problem starts when context grows. This article shows a full context engineering system built in pure Python that contr...
What if a language model had never heard of the internet, smartphones, or even World War II? That’s not a hypothetical — it’s exactly what a team of researchers led by Nick Levine,...
What is llm-d? llm-d is an open source solution for managing high-scale, high-performance Large Language Model (LLM) deployments. LLMs are at the heart of generative AI – so when y...
Researchers from NUS, MIT, and A*STAR propose MEMO, a modular framework that encodes corpus knowledge into a separate trainable MEMORY model. The post MEMO: A Modular Framework for...
Large Language Models ExplainedContinue reading on Medium »
<p>Not every task needs the biggest model. A 4-billion parameter model can sort your notifications just as well as a</p>
Multi-model LLM orchestration is the practice of routing AI requests to different models based on what each task needs — speed, cost, reasoning depth, or code quality. OpenRouter m...
Working with LLMs in Practice Large Language Models are becoming part of everyday data science work. But using them through chat interfaces is only one part of the picture. In this...
Pity the poor large language model!
Most LLM evaluation systems rely on vague scoring and human judgment disguised as metrics. I built a lightweight evaluation layer in pure Python that turns LLM outputs into reprodu...
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