AI圈报教程 / 实战普通
I fine-tuned Qwen3.6 on Tinker to read my neighbours’ khata: 98% credit/payment accuracy for $0.38
内容摘要
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle ...
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教程 / 实战普通
🔬 J'ai mappé les offres d'emploi public de l'OPT-NC avec le référentiel ESCO à l'aide d'embeddings et de Qwen3-32B-AWQ
❔ Contexte Avant de me lancer de l'organisation du HackAVP : 🏆 #HackAVP, premier...
信息来源：DEV Community · Qwen
教程 / 实战普通
From Messy WhatsApp Chits to GST Invoices in 15s — Local AI with Ollama & Qwen 2.5
BahiPilot: The Local-First AI Back Office for Bharat's Wholesalers This is a submission...
信息来源：DEV Community · Qwen / Ollama
教程 / 实战普通
Fine-Tuning Qwen3-8B with Tinker: From 50% to 76% Accuracy, and Burning Through My Budget
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Oktoberfest?...
信息来源：DEV Community · Qwen
教程 / 实战普通
How I Built a Fully Local AI Coding Agent with Qwen 3.8, LM Studio, and Pi (No Paid APIs)
What if you could have an AI coding agent that reads your files, writes code, executes commands, and...
信息来源：DEV Community · Qwen
教程 / 实战普通
I Distilled a 397B Model Into a 4B One for $1.60. It Now Catches 28 of 33 Park Alerts That Should Stop Your Hike.
A Qwen3.5-4B LoRA trained on Tinker reads all 627 live National Park Service alerts, is graded against the rangers' own labels, and prints one go/no-go trail card a week. Then it stops talking.
信息来源：DEV Community · Qwen
教程 / 实战普通
WildQuest: Offline Nature Quests with On-Device Qwen AI
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass ...
信息来源：DEV Community · Qwen
教程 / 实战普通
Multi-Reward RL, Part 3: GDPO + CISPO + REPO-R at 27B, and the Advantage Floor That Stopped Learning
Qwen3.8-27B, 600 steps, 12 reward channels: CISPO, REPO-R and prompt filtering lifted holdout from −0.47 to +1.80, and an advantage floor silently zeroed 96% of the signal.
信息来源：DEV Community · Qwen
教程 / 实战普通
Seu classificador de intenções é 12 pontos pior em português: um benchmark de Laya, Strands Decider e embeddings Qwen3
Um benchmark reprodutível de pequenos modelos de decisão e de embeddings para classificar o objetivo do cliente em português do Brasil, e o que uma tradução paralela para o inglês revela sobre o custo do idioma.
信息来源：DEV Community · Qwen
教程 / 实战普通
Your intent classifier is 12 points worse in Portuguese: benchmarking Laya, Strands Decider and Qwen3 embeddings
A reproducible benchmark of small choice deciders and embeddings for customer-goal classification in Brazilian Portuguese, plus what a parallel English translation reveals about the cost of language.
信息来源：DEV Community · Qwen
教程 / 实战普通
Fine-tuning Qwen2.5-1.5B on a Mac to fix a parroting chatbot (and halve the prompt)
By Georgii Kharlampiiev, Mindscend Our company website is a single chat page backed by a model we...
信息来源：DEV Community · Qwen