
Documento originale
GPT Image 2 · en
{
"type": "Cute Educational Infographic Posters",
"topic": "{argument name=\"headline text\" default=\"Training process of large language models\"}",
"subtitle": "{argument name=\"subtitle text\" default=\"Learn from massive amounts of data and become a super chatty assistant!\"}",
"style": {
"overall": "Adorable Chinese science posters, a soft classroom infographic style, rounded corners, a cream-colored background, hand-drawn cartoon aesthetics, simple vector illustrations, and a warm and friendly educational tone.",
"palette": [
"Cream",
"Lavender Purple",
"Sky blue",
"Mint Green",
"Yellow Orange",
"pink",
"Soft brown"
],
"rendering": "High-quality flat illustrations with delicate shadows, clear Chinese typography, sticker-style decorations, stars, hearts, arrows, and speech bubbles."
},
"layout": {
"format": "Horizontal poster",
"grid": {
"rows": 2,
"columns": 4,
"count": 8
},
"sections": [
{
"title": "1. Data Collection",
"position": "Top left corner",
"count": 1,
"labels": [
"Web page",
"news",
"dialogue"
]
},
{
"title": "2. Data Preprocessing",
"position": "Top row, second column",
"count": 1,
"labels": [
"The weather is so nice today!!",
"The weather is really nice today!!"
]
},
{
"title": "3. Pre-training",
"position": "Top row, third column",
"count": 1,
"labels": [
"Today's weather",
"very good",
"good",
"?",
"......"
]
},
{
"title": "4. Supervised Fine-tuning (SFT)",
"position": "Top right corner",
"count": 1,
"labels": [
"Q: Why does the sun emit light?",
"A: Because...",
"Good answer!"
]
},
{
"title": "5. Reward Model Training (RM)",
"position": "bottom row, first column",
"count": 1,
"labels": [
"Answer A is better!",
"Answer B is so-so."
]
},
{
"title": "6. Reinforcement Learning (RLHF)",
"position": "bottom row, second column",
"count": 1,
"labels": [
"Reward +1",
"Punishment -1"
]
},
{
"title": "7. Evaluation and Testing",
"position": "bottom row, third column",
"count": 1,
"labels": [
"Knowledge and Ability",
"Reasoning ability",
"Security",
"stability"
]
},
{
"title": "8. Deployment and Application",
"position": "bottom right corner",
"count": 1,
"labels": [
"chat",
"Write code",
"Writing articles"
]
}
],
"topDecorations": {
"count": 4,
"items": [
"The small flash in the upper left corner",
"Pink confetti around the title",
"The cute white mascot holding a star wand in the upper right corner",
"A speech bubble that says \"Go for it!\""
]
},
"bottomDecorations": {
"count": 4,
"items": [
"The small white mascot wearing a bow tie in the bottom left corner",
"Summary column containing 7 rounded squares and arrows",
"Concluding remarks centered at the bottom",
"A sticky note with encouraging words and a heart in the bottom right corner."
]
}
},
"characters": {
"main mascots": {
"count": 4,
"types": [
"A round, white bear mascot with pink cheeks",
"Small round robot with a dark face screen and green antenna",
"A human teacher girl with a ponytail",
"A furry white character holding a magnifying glass"
]
},
"recurring_robot_design": "A short, cute robot with a rounded body, a light green and cream-colored shell, a dark blue facial display with glowing eyes, and tiny limbs."
},
"sectionDetails": [
{
"title": "1. Data Collection",
"panelColor": "Lavender Purple",
"scene": "A white mascot wearing a purple hat sits beside a pile of colorful books, using a laptop; floating rounded labels indicate the internet source.",
"caption": "The more data you have, the more knowledge you gain!"
},
{
"title": "2. Data Preprocessing",
"panelColor": "Sky blue",
"scene": "The mascot, wearing a blue hat, swept the scattered scraps of paper into a bin; jumbled sentences were transformed into clearly structured text, complete with arrows.",
"caption": "Transform the dirty and messy into a neat and tidy place."
},
{
"title": "3. Pre-training",
"panelColor": "Mint Green",
"scene": "The robot is reading an open green book, with speech bubbles around it displaying simple words and responses, suggesting a language learning process.",
"caption": "Just like a child learning to speak!"
},
{
"title": "4. Supervised Fine-tuning (SFT)",
"panelColor": "Golden yellow",
"scene": "The teacher pointed to a labeled question-and-answer card, with a cute mascot listening attentively; emphasizing the high-quality question-and-answer pairs with manual annotations.",
"caption": "Learning with a teacher leads to more reliable answers!"
},
{
"title": "5. Reward Model Training (RM)",
"panelColor": "pink",
"scene": "The robot stands between a green checkmark and a red cross, comparing the two answer options to determine which is better.",
"caption": "Learn to \"choose the right answer\"!"
},
{
"title": "6. Reinforcement Learning (RLHF)",
"panelColor": "Lavender Blue",
"scene": "The robot holds tools, and the reward items display positive and negative score feedback with arrows.",
"caption": "Encourage the good and correct the bad!"
},
{
"title": "7. Evaluation and Testing",
"panelColor": "blue",
"scene": "A furry, white-clad examiner stands next to a checklist with four green checkmarks, holding a magnifying glass.",
"caption": "Comprehensive medical examination to ensure quality!"
},
{
"title": "8. Deployment and Application",
"panelColor": "Soft pink",
"scene": "Icons for applications such as chat, writing, code, and documents appeared around the robot, showcasing a real-world deployment scenario.",
"caption": "Officially on duty, here to chat and write with you!"
}
],
"bottomSummary": {
"title": "In summary:",
"count": 7,
"steps": [
"Laying a solid foundation for data collection",
"Preprocessing and organizing data",
"Pre-training knowledge",
"Supervisory fine-tuning school answers",
"Reward models learn to judge",
"Reinforcement learning aligns with human preferences",
"Evaluation and testing quality control"
],
"closingText": "{argument name=\"closing sentence\" default=\"This is the growth path of the large language model from "knowing nothing" to "super learner"! ٩(๑^o^๑)۶\"}"
},
"language": "Simplified Chinese",
"quality": "Beautifully designed infographics suitable for social media posting, with a balanced layout, clear and easy-to-read Chinese text, an appealing style, and high shareability."
}Come usare
- Copia tutto il prompt originale, inclusi i parametri.
- Adatta soggetto, testo e composizione alle tue esigenze.
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