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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...
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.
Fine-tuning large language models isn’t a one-size-fits-all exercise anymore. What started as a technique mostly discussed in AI research…Continue reading on Medium »
To train a large language model (LLM), you need to adjust its learned parameters by presenting it with tokenized text, [...] Read More... The post How to train an LLM appeared firs...
Chinese company Z.ai, which created the GLM models, has launched a legal-specific LLM that has been ‘mid-trained’ and post-trained to handle a range of tasks ...
In this article, you will learn how LLM inference optimization works and which techniques to apply to make language models faster, cheaper, and more reliable...
Removing components one at a time from a high-scoring modelContinue reading on Medium »
So you want your own pet LLM huh? Knowing where to start can be quite tricky, so luckily for you I’ve put together this end-to-end guide. It’ll get you not just started; you’ll end...
A curated, linear pipeline of high-signal free resources that takes you from backpropagation basics to deploying production-grade LLM applications.
Обычно, когда выбирают LLM, сначала смотрят рейтинги. Проблема рейтингов в том, что по ним не узнать, как модель справится с вашими задачами и сколько это будет стоить.В нашей лаб...
Fine-tuning teaches a small search agent your tools and environment, giving it the reliability of a frontier model at lower latency and cost. In this post, we fine-tune an LLM-powe...
Viktoria Semaan of Databricks on running 16 models through one eval set, why Gemma 12B matched Sonnet at a fraction of the cost, and when fine-tuning pays.
Want to understand what makes LLMs fast? Build the systems yourself.
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...
A new benchmark finds that LLMs struggle to complete legal research tasks on their own, even as users pay a premium for the most advanced models.
Llama 3 is a capable generalist, but that's exactly the problem when you need an agent that reliably outputs structured JSON for a specific API.
11 LLM evaluation tools compared for 2026: what each one measures, where it fits in the lifecycle, and how to pick one for your architecture and privacy needs.
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...
Large language models have become easier to integrate into applications, but running them efficiently is still a major engineering challenge. As the number of users and requests in...
How LLM hallucination detection works: groundedness scoring, semantic entropy, judge models and fine-tuned detectors compared, with where each one fails.
On 28 September Unsloth began serving Laya, an open decision model, at a Jev-compatible endpoint on a CPU. On 7 October it shipped…Continue reading on Medium »
Prompt caching, model routing, RAG trimming and batching: a practical LLM cost optimization playbook that keeps quality intact.Continue reading on Medium »
Continue reading on Medium »
Discover what it takes to engineer production-ready LLM applications in an exclusive live session with Prof. Travis D. Breaux, Associate Professor of Computer Science at Carnegie M...
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