Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
20230322 - Generative AI 小聚 ft. Happy Designer
Search
蒼時弦や
March 22, 2023
Technology
510
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
20230322 - Generative AI 小聚 ft. Happy Designer
TLDR
蒼時弦や
March 22, 2023
More Decks by 蒼時弦や
See All by 蒼時弦や
2024 - COSCUP - Clean Architecture in Rails
elct9620
2
230
2023 - RubyConfTW - Rethink Rails Architecture
elct9620
0
290
20230916 - DDDTW - 導入 Domain-Driven Design 的最佳時機
elct9620
0
520
2023 - WebConf - 選擇適合你的技能組合
elct9620
0
750
2022 - 默默會 - 重新學習 MVC 的 Model
elct9620
1
530
MOPCON 2022 - 從 Domain-Driven Design 看網站開發框架隱藏
elct9620
1
550
2022 - COSCUP - 我想慢慢寫程式該怎麼辦?
elct9620
0
330
2022 - COSCUP - 打造高速 Ruby 專案開發流程
elct9620
0
370
2021 - RubyKaigi - It is time to build your mruby VM on the microcontroller?
elct9620
0
330
Other Decks in Technology
See All in Technology
Amazon Bedrock Agents ClassicからAmazon Bedrock AgentCoreへ移行した際、ガードレール設定が2箇所に割れた話
matsunobu
0
160
高負荷プロダクション環境におけるAWS Lambdaのリアル 〜スケールとコストを左右する実行ライフサイクルの技術仕様〜
maimyyym
2
830
雪かき部 #7 もう怖くない!SELECT文!
foursue
0
260
[Kiro Meetup #7] Kiro Crew Dive Deep
konippi
0
440
Argo CDとAtlantisで実現するインフラ管理のセルフサービス化──小規模SREチームで支えるプラットフォーム
cassius7
0
260
生成AIを使って「人が」考える技術 ― AI時代の人機共想と実践ノウハウ|UNITT AC2026
ishiirikie
0
470
認知負荷を吸収し、プロダクトをまたぐPR Preview基盤の設計事例
taiki45
2
550
Harness Engineering on Rails
joelq
0
770
Coil3を内部実装から読み解く~キャッシュ戦略とAVIF画像の描画〜/nikkei-tech-talk50
nikkei_engineer_recruiting
0
180
行動するAIのためのオントロジー | DevRev — Encraft #26.pdf
dvrv_tknrszk
2
630
HolmesGPTで始めるSREエージェント入門!プラットフォームの障害調査はAIにお任せ 〜
leveragestech
PRO
0
120
セルフサービスのオブザーバビリティ基盤をOpenTelemetryで作る / Building a Self-Service Observability Platform with OpenTelemetry
ymotongpoo
3
490
Featured
See All Featured
Measuring & Analyzing Core Web Vitals
bluesmoon
9
1k
AI: The stuff that nobody shows you
jnunemaker
PRO
10
1.1k
What’s in a name? Adding method to the madness
productmarketing
PRO
24
4.2k
Evolution of real-time – Irina Nazarova, EuRuKo, 2024
irinanazarova
9
1.6k
The #1 spot is gone: here's how to win anyway
tamaranovitovic
4
1.2k
The Power of CSS Pseudo Elements
geoffreycrofte
82
6.6k
Darren the Foodie - Storyboard
khoart
PRO
4
4k
Creating an realtime collaboration tool: Agile Flush - .NET Oxford
marcduiker
35
2.6k
Navigating Weather and Climate Data
rabernat
0
540
Jamie Indigo - Trashchat’s Guide to Black Boxes: Technical SEO Tactics for LLMs
techseoconnect
PRO
0
690
Improving Core Web Vitals using Speculation Rules API
sergeychernyshev
21
1.6k
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
danielanewman
230
23k
Transcript
除了串 API 之外工程師還能做些什麼 Generative AI Meetup ft. Happy Designer
蒼時弦也 Software Developer https://blog.aotoki.me
開始之前 生態系進化太快,都不知道該怎麼辦⋯⋯
Diffusers 簡單使用 Stable Diffusion 的方法
Hugging Face AI 領域的 GitHub,大部分開源模型都可以在上面找到
import from import = = = = = torch diffusers
StableDiffusionPipeline pipe StableDiffusionPipeline.from_pretrained( , torch.float16) pipe pipe.to( ) prompt image pipe(prompt).images[ ] # 載入模型 # 進行運算 "runwayml/stable- diffusion-v1-5" "cuda" "a photo of an astronaut riding a horse on mars" torch_dtype 0
# ... # 載入不同模型 # 多重處理 prompt image txt2image(prompt).images[ ]
image upscale(image).images[ ] image image2image(image).images[ ] = = = = "a photo of an astronaut riding a horse on mars" 0 0 0
None
http://bit.ly/3JJf16o
Replicate 目前最好用的 Serverless GPU 服務
None
from import import class def def = = = =
= return cog BasePredictor, Path, Input torch ( ): (self): (self, image: Path Input( ), scale: Input( , ) ) -> Path: output Predictor BasePredictor setup predict # 初始化、載入模型 # 處理 e.g. Stable Diffusion Pipeline description description default "Image to enlarge" "Factor to scale image by" float 1.5
$ $ cog login cog push r8.im your username your
model name /< - >/< - - >
有 GPU 的伺服器、API 都有了,剩下就是套應用
AI Gacha 使用 Diffusers、Replicate 的實驗性專案
None
http://bit.ly/3yImmgc
我的看法 能做的事情其實不多,大部分應用的成本也偏高,但是商用已經沒 有問題,剩下要處理的大概會在 跟讓更多人能 合法的版權 輕鬆上手