How to use PHPStorm to debug a Laravel Project
The system has already been deployed to my customer since 2015. The system still works very well. But sometimes I still receive my customer call. I need to restore database …
在自己的電腦上運行本地 LLM 推理研習環境
類似 ChatGPT，但可以在你的電腦上運行 這篇文章將教你如何在自己的電腦上建立 本地 LLM 推理環境，使用 Ollama 離線運行大型語言模型。 第一步下載程式 請到網址 https://www.ollama.com/ 下載程式OllamaSetup.exe，並運行程式安裝到你的系統 執行程式 用滑鼠點選系統工具列上的Windows圖示，再到搜尋選單輸入Ollama，你就會看到這個Ollama程式了。請執行它。 下載模型 程式執行後，你先到下圖所示的位置選取所要用的模型，選定模型後可以按下載。 如果沒選取模型後沒有下載，詢問問題後也會下載。 詢問問題 模型的差異 在Ollama的官網上的Models中就可以看到目前Ollama可以用的模型。 像是對岸的deepseek OpenAI的開源模型 現在你已經完成 本地 LLM 推理環境 的搭建，可以開始離線實驗屬於你的 AI 模型。 子五乙的同學可以下載到你的電腦玩看看！
Deploying Your Fine-tuned Hugging Face Model to the Cloud with Modal — in Just One Command
🧭 Introduction: Why Modal? Traditionally, deploying AI models in the cloud is a painful process: Modal completely changes that.It lets you define your infrastructure as code — in pure Python.You …
Learning Transformers the Easy Way with LLaMA 3.2
PyTorch-based LLaMA model architecture The overall architecture of the LLaMA model Waht embed_tokens does Suppose your vocabulary has only 5 words: [“I”, “want”, “to”, “learn”, “English”], Instead of representing them …
兩階段擴散模型設計
（Base → Refiner 粗生成到細化修飾流程）是一種「粗生成 → 細化修飾」的方法，使用 Stable Diffusion XL 生成潛空間影像，再由 Refiner 模型細化紋理與光影，提升影像品質與真實感。 ⚙️ 關鍵參數與流程說明 1️⃣ Base 模型：兩階段擴散模型的粗生成步驟 這裡： → 目的：產生一張粗略但有整體構圖的潛在影像。 2️⃣ Refiner 模型：兩階段擴散模型的細化修飾步驟 這裡： → 目的：讓影像更細膩、真實、視覺品質更高。 🧩 為什麼要分兩階段？ 這樣做的理由主要有三個： 🔍 …
From Meeting Audio to AI-Generated Minutes with Whisper and LLaMA
Writing meeting minutes has always been a time-consuming task. Thanks to advances in AI, we can now automate the process: In this post, we’ll walk through the full workflow. Step …
Efficient Multi-Model Inference with 4-bit Quantization in Hugging Face Transformers
Introduction In this large language model Colab tutorial, I’ll walk you through how to efficiently load and run multiple large language models (LLMs) in Hugging Face Transformers using 4-bit quantization …
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How to Run Hugging Face Models on Google Colab
Hugging Face provides a wide variety of pre-trained models for tasks like text generation, summarization, translation, and more. Google Colab, on the other hand, offers free cloud-based Jupyter notebooks with …
Building an Agentic Chatbot: Memory, Speech, and Image Generation with LLMs
Introduction Mention that this blog demonstrates how to build a chatbot that can respond with text, speech, and images while remembering conversation context. Briefly introduce Agentic AI: LLMs that can …
Extending GPT with External Tools: How AI Can Call APIs for Smarter Answers
Extending OpenAI with External Tools When working with OpenAI models, you might face situations where the model cannot directly provide real-time or domain-specific answers — such as looking up the …