AI圈报教程 / 实战普通
Llama Village: a virtual world powered by local AI with llamadart
内容摘要
Llama Village in motion. The characters’ dialogue is generated by an on-device model. Watch the...
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教程 / 实战普通
llama.cpp vs Ollama — which one should you run?
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llama.cpp vs Ollama: Which Should You Run in 2026?
llama.cpp vs Ollama: Ollama wraps llama.cpp for convenience, raw llama.cpp wins on speed and control. Benchmarks, GPU offload flags, and when each wins.
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教程 / 实战普通
The harness, not the model: how to make a weak or local model reliable enough to ship
If you've tried to point a local model — Qwen, a quantized Llama, whatever fits on your GPU — at a...
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教程 / 实战普通
Fine-tuning Claude vs GPT vs Llama in Production: What Actually Works (2026)
Honest comparison of fine-tuning options across Anthropic, OpenAI, and open-weight models. When fine-tuning wins, when RAG wins, and when prompt engineering is enough - from an Anthropic Partner shipping production ML.
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教程 / 实战普通
I Swept All 33 Bedrock Regions So You Don't Have To
One region out of 33 can fine-tune Llama 3.3 70B on Bedrock. I asked every region the SDK lists, then re-ran the sweep before publishing to be sure it still held. Also in here: every model you can customise in us-east-1 belongs to Amazon, …
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教程 / 实战普通
Beyond Vibes: Architecting Closed-Loop AI Agents with Local SLMs, Deterministic Evals, and Human Learning Loops
How to build a production-grade drafting agent on local SLMs (Llama 3.2 3B) using deterministic Python verification, tri-state guardrails, QWK-calibrated evals, and continuous few-shot learning.
信息来源：DEV Community · Llama
教程 / 实战普通
Run GLM-5.3 Locally: Real Quant Sizes, the llama.cpp Surprise, and the reasoning_effort Trap
Flash on 27 August, the flagship on 28 August. Real quant sizes, why the bigger model has better tooling support than the smaller one, and the default that silently makes it feel slow.
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教程 / 实战普通
Building a 200M parameter LLM from scratch in PyTorch
It's really easy to spin up Unsloth and fine-tune Llama 3 in an afternoon. I wanted to see what...
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教程 / 实战普通
I Tried Needle2 for Local Tool Calling. I Ended Up With llama.cpp + Granite
I’ve been working on a small experiment around a semantic shell. The basic idea is that the user...
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