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📰 Dev.to · Tech_Nuggets

7 articles · Updated every 3 hours · View all reads

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KV cache and PagedAttention: what they do and why they matter
Dev.to · Tech_Nuggets 🧠 Large Language Models ⚡ AI Lesson 2mo ago
KV cache and PagedAttention: what they do and why they matter
An explanation of the KV cache memory problem in production LLM serving and how PagedAttention (the technique behind vLLM) solves it with OS-inspired virtual me
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The Model Context Protocol (MCP): what it is and how to build a server
Dev.to · Tech_Nuggets 🧠 Large Language Models ⚡ AI Lesson 2mo ago
The Model Context Protocol (MCP): what it is and how to build a server
A practical walkthrough of the Model Context Protocol — what it is, how JSON-RPC 2.0 transports work, and how to build an MCP server in Python with FastMCP.
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Structured output from LLMs: JSON mode, function calling, and grammar-constrained decoding
Dev.to · Tech_Nuggets 🧠 Large Language Models ⚡ AI Lesson 2mo ago
Structured output from LLMs: JSON mode, function calling, and grammar-constrained decoding
A practical comparison of three approaches to getting structured data from LLMs: prompt-only JSON, API-level JSON mode and function calling, and grammar-constra
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Sampling strategies compared: temperature, top-p, top-k, min-p, and what actually works in production
Dev.to · Tech_Nuggets 🧠 Large Language Models ⚡ AI Lesson 2mo ago
Sampling strategies compared: temperature, top-p, top-k, min-p, and what actually works in production
A production-oriented comparison of LLM sampling parameters -- how temperature, top-p, top-k, and min-p reshape the output distribution, what combos actually wo
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Quantization formats compared: GGUF vs GPTQ vs AWQ vs NF4
Dev.to · Tech_Nuggets 🧠 Large Language Models ⚡ AI Lesson 2mo ago
Quantization formats compared: GGUF vs GPTQ vs AWQ vs NF4
A practical comparison of the four major LLM weight quantization formats — which one to use for CPU, GPU serving, and fine-tuning, with current version numbers
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LoRA and QLoRA fine-tuning: what they actually do under the hood
Dev.to · Tech_Nuggets 🧠 Large Language Models ⚡ AI Lesson 2mo ago
LoRA and QLoRA fine-tuning: what they actually do under the hood
A practical walkthrough of LoRA and QLoRA -- how low-rank adaptation works, what NF4 quantization brings, and when to use each.
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KV cache quantization: what FP8/INT8 K and V actually buy you, and where they break
Dev.to · Tech_Nuggets 🧠 Large Language Models ⚡ AI Lesson 2mo ago
KV cache quantization: what FP8/INT8 K and V actually buy you, and where they break
FP8 and INT8 KV caches cut attention state ~50%, but they shift the target model's logit distribution — and that can quietly halve the gains from speculative de
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