
かわいい4パネルのトークン化インフォグラフィック
このプロンプトは、2体のマスコットキャラクターが4つのトークン化方法を説明する、手描きの大型インフォグラフィックを生成します。これは、AIとNLPに関するソーシャルメディアの教育投稿に最適です。
これはグラフィック&ポスター向けのGPT Image 2プロンプトケースです。以下のコピー可能なプロンプトを使用して同様のビジュアルを生成し、再利用する前にAwesome GPT Image 2 Prompts帰属表示と商用利用権を確認してください。
プロンプトセット全体が必要ですか? グラフィック&ポスター 関連する例をもっと見るにはトピックハブを開くか、 GPT Image 2 プロンプトカタログ 完全な例の索引、再利用可能な構造、および出典の明記については、こちらをご覧ください。
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プロンプト
コピー準備完了プロンプト
{
"type": "hand-drawn educational infographic illustration",
"style": "cute notebook doodle style, hand-painted handbook aesthetic, warm beige paper background with faint texture, playful sketchy outlines, soft pastel colors, small flower and star doodles, taped paper-card layout",
"aspect_ratio": "wide horizontal",
"subject": {
"characters": [
{
"name": "{argument name=\"dog character name\" default=\"Chai Xiaoqi\"}",
"species": "Shiba Inu mascot",
"appearance": "cute orange-brown Shiba Inu with cream muzzle and belly, round face, upright ears, friendly expression, simplified cartoon anatomy"
},
{
"name": "{argument name=\"blue character name\" default=\"Token\"}",
"species": "blue token mascot",
"appearance": "rounded triangular blue droplet-shaped character with glossy gradient body, tiny arms and legs, rosy cheeks, smiling face, the word \"{argument name=\"token label\" default=\"TOKEN\"}\" written across the body in white"
}
],
"theme": "compare four levels of text segmentation in a friendly science-explainer format"
},
"layout": {
"sections": [
{
"title": "1. Word-level Segmentation",
"position": "far left panel",
"count": 1,
"subtitle": "Divided according to complete semantics",
"scene": "A Shiba Inu and a blue Token character stand next to a basket labeled \"Tokens\", which is filled with slips of paper. Visible slips and labels are written with \"Programmer\", \"Left\", \"Artificial Intelligence\", and a small sign next to it reads \"ProgrammerLeft\". The Token character points to the basket, while the Shiba Inu displays sorted fragments."
},
{
"title": "2. Character-level tokenization",
"position": "left-center panel",
"count": 1,
"subtitle": "Splitting the text character by character",
"scene": "A blue Token character uses a magnifying glass to examine small character blocks scattered on the floor, while a Shiba Inu organizes them nearby. A label strip at the bottom reads \"ProgrammerLeftArtificialIntelligence\", serving as a continuous text sample broken down into individual characters."
},
{
"title": "3. Subword tokenization",
"position": "right-center panel",
"count": 1,
"subtitle": "Divide by root words and prefixes",
"scene": "The Shiba Inu points to a project demonstrating root word splitting and arrows, with a blue Token mascot standing next to it. Small paper labels contain mixed fragments such as \"program\", \"member\", \"Left\", \"artificial\", \"intelligence\", emphasizing morpheme or subword groupings."
},
{
"title": "4. Byte-level tokenization",
"position": "far right panel",
"count": 1,
"subtitle": "Convert to byte encoding combinations for division",
"scene": "the Shiba Inu uses a retro computer with a long printed strip emerging from it, and the blue token character stands to the side. Across the lower half are ribbon-like strips filled with repeated byte numbers and symbols, especially \"1\", \"2\", \"3\", \"4\", and \"-3\", illustrating byte encoding combinations."
}
],
"decorations": {
"count": 10,
"items": [
"4 pieces of taped corners in pale yellow and pink",
"small five-point stars scattered around panels",
"tiny flower doodles between panels",
"curved motion lines near character gestures",
"notebook-style vertical panel dividers",
"rounded rectangular panel frames",
"light shadows behind paper panels",
"faint horizontal paper grain",
"small spark icons",
"hand-drawn accent marks"
]
}
},
"composition": "four equal vertical panels arranged left to right across one canvas, each panel with a bold numbered Chinese heading and a smaller subtitle beneath it, each panel showing the two mascots acting out a different tokenization concept",
"text": {
"headings": [
"1. Word-level Segmentation",
"2. Character-level tokenization",
"3. Subword tokenization",
"4. Byte-level tokenization"
],
"subtitles": [
"Divided according to complete semantics",
"Splitting the text character by character",
"Divide by root words and prefixes",
"Convert to byte encoding combinations for division"
]
},
"quality": "clean, polished, adorable, presentation-ready educational visual",
"use_case": "social media science explainer comparing tokenization methods for AI and NLP"
}プロンプト変数
プロンプトに表示される編集可能な引数プレースホルダーと、それらのデフォルト値。
変数
dog character name
デフォルト
Chai Xiaoqi
変数
blue character name
デフォルト
Token
変数
token label
デフォルト
TOKEN
Best for
- - グラフィック&ポスター visual exploration
- - Image generation and reference-image edits
- - Reusable briefs that keep source attribution visible
Change these parts
- - Subject, product, character, or scene
- - Aspect ratio, camera, lighting, and background
- - Brand, text, color, and output constraints
Recommended model and settings
- - Model: gpt-image-2
- - Input mode: 画像から画像
- - Aspect ratio: source
- - Commercial status: review original source
How to use this prompt
- 1. Copy the prompt and preserve its structure for the first test.
- 2. Replace the subject, context, and publishing channel.
- 3. Change one camera, lighting, or style variable per iteration.
- 4. Inspect the output, source, text, and rights before reuse.
Limitations, source, and reuse cautions
- - Generated output is an editable draft, not factual, legal, or rights evidence.
- - Review the linked source, people, brands, logos, text, and third-party media before commercial use.
Awesome GPT Image 2 Promptsからインポートされました。出典の明記が必要です。商用利用の可否はallowedです。有料利用の前に、出典元の権利をご確認ください。
このカテゴリーのその他の事例
カテゴリー、入力モードの互換性、品質、およびリスクの低さに基づいて優先順位付けされています。
再利用と出典に関する注記
ケースを事前に確認してから、このプロンプトを安全に使用してください。
- 1.プロンプトをコピーするか、生成ボタンを使ってDovooで直接開いてください。
- 2.ご自身の用途に合わせて、変数、アスペクト比、および参照画像を調整してください。
- 3.公開または有料利用の前に、情報源の権利、帰属表示の要件、およびブランドまたは肖像権に関するリスクを確認してください。





