Stable Diffusion XL Refiner 細化修飾結果

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: 🔍 …

How to Run Hugging Face Models on Google Colab [Step-by-Step Guide]

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 …

Gradio

GPT and Claude In Gradio UI

Gradio is an open-source Python framework that makes it easy to build interactive web-based UIs for machine learning (ML) models, data pipelines, or any Python function. Instead of writing frontend …

From One-Shot to Multi-Shot Prompting

One-Shot The Website class retrieves the text content and links from a given URL. Prompt 1: Here’s an OpenAI example showing how to use a one-shot prompt to get a …