17

可爱的中文大语言模型训练流程图
Enlarge

可爱的中文大语言模型训练流程图

Prompt
{"type":"cute educational infographic poster","topic":"{argument name=\"headline text\" default=\"大语言模型的训练过程\"}","subtitle":"{argument name=\"subtitle text\" default=\"从海量数据中学习,变成\"超会聊天\"的小助手!\"}","style":{"overall":"adorable Chinese explainer poster, pastel classroom infographic, rounded panels, soft cream background, hand-drawn cartoon aesthetic, clean vector-like illustration, warm friendly educational tone","palette":["cream","lavender","sky blue","mint green","yellow-orange","pink","soft brown"],"rendering":"high-quality flat illustration with subtle shading, crisp Chinese typography, sticker-like accents, tiny stars, hearts, arrows, and speech bubbles"},"layout":{"format":"horizontal poster","grid":{"rows":2,"columns":4,"count":8},"sections":[{"title":"1. 数据收集","position":"top-left","count":1,"labels":["网页","新闻","对话"]},{"title":"2. 数据预处理","position":"top row, second column","count":1,"labels":["今天 天气 真不错!!","今天|天气|真|不错!!"]},{"title":"3. 预训练","position":"top row, third column","count":1,"labels":["今天气","很好","不错","?","......"]},{"title":"4. 监督微调(SFT)","position":"top-right","count":1,"labels":["问:太阳为什么会发光?","答:因为……","好回答!"]},{"title":"5. 奖励模型训练(RM)","position":"bottom-left","count":1,"labels":["回答A 更好!","回答B 一般般"]},{"title":"6. 强化学习(RLHF)","position":"bottom row, second column","count":1,"labels":["奖励 +1","惩罚 -1"]},{"title":"7. 评估与测试","position":"bottom row, third column","count":1,"labels":["知识能力","推理能力","安全性","稳定性"]},{"title":"8. 部署与应用","position":"bottom-right","count":1,"labels":["聊天","写代码","写文章"]}],"topDecorations":{"count":4,"items":["small sparkle at upper left","pink confetti strokes around title","cute white mascot at upper right holding star wand","speech bubble saying 冲鸭!"]},"bottomDecorations":{"count":4,"items":["small white mascot with bow tie at lower left","summary strip with 7 rounded mini boxes and arrows","centered closing sentence at bottom","sticky note at lower right with encouraging text and heart"]}},"characters":{"main mascots":{"count":4,"types":["white chubby bear-like mascot with pink cheeks","small round robot with dark face screen and green antenna","human teacher girl with ponytail","fluffy white character with magnifying glass"]},"recurring_robot_design":"short cute robot, rounded body, pale green and cream shell, navy face display with glowing eyes, tiny limbs"},"sectionDetails":[{"title":"1. 数据收集","panelColor":"lavender","scene":"a white mascot wearing a purple cap uses a laptop while sitting beside a stack of colorful books; floating rounded labels represent internet sources","caption":"数据越多,知识越丰富!"},{"title":"2. 数据预处理","panelColor":"sky blue","scene":"the mascot in a blue cap sweeps scattered paper scraps into a bucket; a messy sentence is transformed into segmented clean text with an arrow","caption":"把脏乱差,变得整整齐齐~"},{"title":"3. 预训练","panelColor":"mint green","scene":"the robot reads an open green book while speech bubbles around it show simple tokens and responses, suggesting language learning","caption":"像小朋友学习说话一样!"},{"title":"4. 监督微调(SFT)","panelColor":"golden yellow","scene":"a teacher points to a labeled QA card while a cute mascot listens; emphasis on human-labeled high-quality question-answer pairs","caption":"老师带着学,回答更靠谱!"},{"title":"5. 奖励模型训练(RM)","panelColor":"pink","scene":"the robot stands between a green check mark and a red X, comparing two answer options to learn which is better","caption":"学会\"挑好答案\"!"},{"title":"6. 强化学习(RLHF)","panelColor":"lavender-blue","scene":"the robot holds tools while a reward board shows positive and negative score feedback with arrows","caption":"鼓励好的,改掉不好的!"},{"title":"7. 评估与测试","panelColor":"blue","scene":"a fluffy white examiner character holds a magnifying glass beside a clipboard checklist with four green check marks","caption":"全方位体检,确保质量过关!"},{"title":"8. 部署与应用","panelColor":"soft red-pink","scene":"the robot appears surrounded by application icons for chat, writing, coding, and documents, showing real-world deployment","caption":"正式上岗,陪你聊天写作啦!"}],"bottomSummary":{"title":"总结一下:","count":7,"steps":["数据收集 打好基础","预处理 整理数据","预训练 学知识","监督微调 学会回答","奖励模型 学会评判","强化学习 对齐人类偏好","评估测试 质量把关"],"closingText":"{argument name=\"closing sentence\" default=\"这就是大语言模型从\"啥也不懂\"到\"超级学霸\"的成长之路!٩(๑^o^๑)۶\"}"},"language":"Simplified Chinese","quality":"polished social-media-ready infographic, balanced spacing, legible Chinese text, charming and highly shareable"}
Category
Charts & Infographics
Model
GPT Image 2
Views2
Source ID
14665
Published
Apr 21, 2026

Guide

About "可爱的中文大语言模型训练流程图"

What is this prompt for?

"可爱的中文大语言模型训练流程图" AI image prompt for GPT Image 2 (Charts & Infographics). 一张柔和色调的中文教育海报,通过 8 个可爱的吉祥物场景,生动解释了大语言模型的训练流程,非常适合社交媒体科普或 AI 入门教学。 Copy it on Picva a…

The full copyable prompt and example visuals above are ready for AI image generation or one-click recreate in Picva.

How to use this prompt

  1. Step 1

    Open the prompt detail

    Review the example visuals, category, and full prompt text for "可爱的中文大语言模型训练流程图".

  2. Step 2

    Copy the prompt

    Copy the prompt body from this page, or load it directly in Studio.

  3. Step 3

    Pick a model (GPT Image 2)

    Prefer GPT Image 2. If you switch models, keep subject and composition and tweak style terms.

  4. Step 4

    Generate and export

    Recreate the look in Picva, or export into your workflow for editing and publishing.

FAQ

What is the "可爱的中文大语言模型训练流程图" prompt?
It is an AI image-generation prompt for GPT Image 2 in the Charts & Infographics category. This page includes the full prompt text, example visuals, and a one-click recreate path in Picva.
How do I use this prompt to generate an image?
Copy the prompt from this page, or use Generate / Studio. Paste it into a compatible image model, or recreate the look in Picva with optional reference images.
Which model is this prompt for?
This page lists GPT Image 2. Most descriptive prompts also transfer to nearby image models such as GPT Image, Flux, or Midjourney with light style tweaks.
Can I use the result commercially?
You can usually copy the prompt for creation, but commercial use of the final image depends on the model terms, reference-image rights, and the generated content. Follow the source author and platform rules.