What is vLLM?
Demystifying its use cases in complete detail, with a discussion of its competitors & a detailed comparison among all of them! As a bonus…Continue reading on Medium »
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Demystifying its use cases in complete detail, with a discussion of its competitors & a detailed comparison among all of them! As a bonus…Continue reading on Medium »
A small language model runs on ordinary hardware fast enough to serve one user, and an LLM is one that does not. SLM vs LLM compared, with 200 measured runs.
The default assumption in most LLM developer communities is that you start with raw API calls and graduate to a framework as your project grows.
llm.rb is an advanced runtime for building highly capable AI applications on CRuby. This release is packed with new features, bug fixes, & other improvements.
Large Language Models (LLMs) have transformed the way educational platforms deliver personalized learning experiences. Instead of simply displaying static lessons, modern education...
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LLMs generate code incredibly fast, but to ensure they generate exactly what is intended, they need clear boundaries. Abstractions and Domain-Specific Languages (DSLs)...
TL;DR: LLMs and SLMs are two types of language models used in artificial intelligence systems. LLMs are built to handle large-scale tasks with higher reasoning ability, while SLMs...
Qwen3.8–27B 現在是很多人本機跑 coding model 的首選,而大部分人第一個拿起來的工具是 llama.cpp — 簡單、GGUF 原生、跑得動。我們把兩套 stack 放在同一張 RTX 4090 上跑,原本預期 vLLM 會...
LLM observability makes an LLM app's behavior visible in production through traces, evaluations, and quality signals. Learn what to monitor and how.
The LLM handles ACES high dynamic range end to end, renders multishot sequences as a single output and runs on a studio's own hardware; available now on Hugging Face, the LTX API a...
Inside a five-stage digest pipeline where the LLM proposes and deterministic code decidesContinue reading on Medium »
A practical guide to LLM evaluation: which metrics matter, how the methods compare, how to build an eval set, and how to gate releases on evals inside CI.
https://github.com/sergey-homenko/llm_cost_tracker
This vllm tutorial shows how to install vLLM, run offline batch inference, expose a local OpenAI-compatible API, and tune the server for production-style LLM workloads. vLLM is use...
Full tensor-level control for custom machine learning models on Android.Continue reading on ProAndroidDev »
Using Gemma 4, Ollama, OpenAI Agents SDK, and Tavily MCP to build a lightweight research agent The post From Local LLM to Tool-Using Agent appeared first on Towards Data Science.
This is the first in a series of build-log posts documenting a local LLM project, in which models are run on owned consumer hardware rather than through a cloud API. The present en...
In this blog post, we will see how an LLM request and response cycle works, from the second you hit send to the moment the last word lands on your screen. I will not throw a wall o...
LLM-as-a-judge scores individual outputs well but can't evaluate a full AI agent conversation. Learn the techniques, code, and biases that make judges reliable.
The open-vs-closed gap has collapsed to roughly 6–9 months.Continue reading on Medium »
An LLM agent is an AI system that combines a large language model with planning, memory, and external tools to [...] Read More... The post What is an LLM agent? appeared first on H...
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