Stan Chan retweetledi
Stan Chan
6.5K posts

Stan Chan
@ciyai1
Maker | Senior UI/UX Designer | Senior Frontend Developer
CHINA Katılım Temmuz 2011
249 Takip Edilen128 Takipçiler
Stan Chan retweetledi

Transformers.js v3 is finally out
- WebGPU support (up to 100x faster than WASM)
- New quantization formats (dtypes)
- 120 supported architectures in total
- 25 new example projects and templates
- Over 1200 pre-converted models
- Node.js (ESM + CJS), Deno, and Bun compatibility
- A new home on GitHub and NPM
English
Stan Chan retweetledi

A warm welcome to Moonshine, a new family of speech-to-text models!
Moonshine claims to be as fast and accurate as whisper-base, while being up to 5x faster! 🤯
They achieve this by removing whisper's constraint on 30-second length audios. Instead, Moonshine processes audios of any length. 🧠
I will be trying this with our speech-to-speech pipeline and reporting back the results. So far, I'm sad not to see an MLX native implementation.

English
Stan Chan retweetledi
Stan Chan retweetledi

Announcing Rspack 1.0 - the next generation JavaScript bundler written in Rust, webpack compatible, 10x faster.
Check out the release blog for more details:
rspack.dev/blog/announcin…
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Stan Chan retweetledi

Using components like <Card.Body> ?
❌ Avoid this: code can't tree shake 😅
- Card.Body = function() {...}
- Object.assign(Card,{Body})
✅ Use ESM-named exports instead!
- export function Body() {}
- import {Body} from "./card"
Libs doing this well: Chakra, Radix

Ivica Batinić@_isBatak
Finally found the time to write a blog post! 📝 Check out ivicabatinic.from.hr/posts/multipar… to see how to create multipart components with dot notation, supporting RSC and better tree shaking. Learned about this from Chakra UI’s source code! #React @webDev #RSC #TreeShaking #ChakraUI
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Stan Chan retweetledi
Stan Chan retweetledi

Online demos for BiRefNet on @huggingface Spaces!
Is this the best background removal model out there? 🤯
MIT licensed. 5.5G GPU memory needed for inference for 1024x1024 images.🤩
English
Stan Chan retweetledi

Anthropic (@AnthropicAI) just announced a game-changer for their API: Prompt caching.
Think of prompt caching like this: You're at a coffee shop. The first time you visit, you need to tell the barista your whole order. But next time? Just say "the usual."
That's prompt caching. Here's why it's a big deal...
It makes it cheaper and faster to call any large prompt components that you reference over and over again.
Specifically? Up to 90% cost reduction. 85% faster responses. Use cases are wild.
Think:
•Cheap conversations with chatbots that have encyclopedic knowledge
•Coding assistants that can efficiently read your entire codebase
•AI that can discuss entire books at crazy low latencies and costs
It means a bunch of AI-powered apps that were previously too expensive to run just became viable.

English
Stan Chan retweetledi

You can now fine-tune your own FLUX.1 text-to-image AI on Replicate, with just a few images.
Teach the model to generate a character, pet, style, or anything else.
@fofrAI even trained one on "bad 70s food". See it in action, and learn to do it too 👇
replicate.com/blog/fine-tune…
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Stan Chan retweetledi

SREF CODES COLLECTION. UPD
Midjourney v6.2 will be a bigger release than v6.1. It will likely drop soon — no official date has been announced, but I’m guessing September or even earlier, as Midjourney often surprises us 🙂
I've decided not to update my collection for v6.1 as planned since it doesn't make sense. Instead, I’ll send you the update for v6.2.
In the meantime, if you haven't purchased it yet, you can download the sref codes collection with prompt examples at a 30% discount.
Use the code: 30
The link is in the thread.
→ 70 Styles
→ 280 Prompt Examples
→ 1120 Images (you can download all images from the PDF). Most of the images have resolution 896 × 1344 and some of them 928 × 1232.
→ Constantly Updating 🟢 (next update in September)
Just change --v 6.0 to --v 6.1 for even better results. You can also add my personal code --personalize kzilt9y to get cleaner images.
Enjoy!

English
Stan Chan retweetledi
Stan Chan retweetledi

🌎 Hola, Bonjour, こんにちは! Introducing AI-powered Localization for your website. Effortlessly translate your entire site, customize images, and even tweak entire designs for different languages and regions. Learn more about Localization at framer.com/updates/locali…
日本語
Stan Chan retweetledi

CSS Trick 🖼️
You could take the resize trick from last week and use it to create one of those sliding image components 👀
CSS only, JavaScript to enhance later 🤓
Put an image in each panel and make them position: absolute. They can use a container query unit for their size 🫶
img {
position: absolute;
width: 100cqi; // Make them the container width 🤙
}
.panel:last-of-type img {
right: 0;
}
The rest of the trick from last week was using display:grid with grid-template-columns. Then we have a resizable element inside the first column 😎
.panels{
display: grid;
grid-template-columns: auto 1fr; 👈
}
.resizer{
max-width: 100cqi;
overflow: hidden;
resize: horizontal; 👈
}
Where does JavaScript come in? To progressively enhance the thing with keyboard controls ✨ Not 100% sure of the pattern for that though. Feels like it should be a button that you can toggle into resize mode and then use left/right to resize 🤔
Anyways, @CodePen link below! 👇
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Stan Chan retweetledi

Stability AI is proud to Introduce Stable LM 3B: Bringing Sustainable, High-Performance Language Models to Smart Devices.
Download the weights on Hugging Face today 🌟🚀 #StabilityAI #StableLM3B #LanguageModels bit.ly/3thtyAJ

English
Stan Chan retweetledi
Stan Chan retweetledi

You can now get a full tracing/observability UI in *all* @llama_index RAG/agent pipelines, in one-line of code ⚡️
Bonus: all your data lives locally! 🔐
We're launching a native integration with @arizeai Phoenix 🔥. Full 🧵 below.
Full Colab nb: colab.research.google.com/github/Arize-a…
English
Stan Chan retweetledi

Explaining 8 Popular Network Protocols in 1 Diagram. The method to download the high-resolution PDF is available at the end.
Network protocols are standard methods of transferring data between two computers in a network.
1. HTTP (HyperText Transfer Protocol)
HTTP is a protocol for fetching resources such as HTML documents. It is the foundation of any data exchange on the Web and it is a client-server protocol.
2. HTTP/3
HTTP/3 is the next major revision of the HTTP. It runs on QUIC, a new transport protocol designed for mobile-heavy internet usage. It relies on UDP instead of TCP, which enables faster web page responsiveness. VR applications demand more bandwidth to render intricate details of a virtual scene and will likely benefit from migrating to HTTP/3 powered by QUIC.
3. HTTPS (HyperText Transfer Protocol Secure)
HTTPS extends HTTP and uses encryption for secure communications.
4. WebSocket
WebSocket is a protocol that provides full-duplex communications over TCP. Clients establish WebSockets to receive real-time updates from the back-end services. Unlike REST, which always “pulls” data, WebSocket enables data to be “pushed”. Applications, like online gaming, stock trading, and messaging apps leverage WebSocket for real-time communication.
5. TCP (Transmission Control Protocol)
TCP is is designed to send packets across the internet and ensure the successful delivery of data and messages over networks. Many application-layer protocols build on top of TCP.
6. UDP (User Datagram Protocol)
UDP sends packets directly to a target computer, without establishing a connection first. UDP is commonly used in time-sensitive communications where occasionally dropping packets is better than waiting. Voice and video traffic are often sent using this protocol.
7. SMTP (Simple Mail Transfer Protocol)
SMTP is a standard protocol to transfer electronic mail from one user to another.
8. FTP (File Transfer Protocol)
FTP is used to transfer computer files between client and server. It has separate connections for the control channel and data channel.
–
Subscribe to our newsletter to download the high-resolution PDF. After signing up, find the download link on the success page: bytebytego.ck.page/3581072b8e
English
Stan Chan retweetledi

Multi-document agents 🤖
Today we released an initial architecture aimed at generalizing RAG to more documents and more question types 📑🔎
Check out this amazing diagram by @clusteredbytes outlining the core agent/retrieval components!
Full guide here: gpt-index.readthedocs.io/en/latest/exam…
Rohan@rsrohan99
Multi Document Agent architecture (v0) in @llama_index, a step beyond naive top-k RAG. It allows answering broader set of questions over multiple documents, which weren't possible with basic RAG. Let's break down the agent architecture and see how it works 👇🧵
English
Stan Chan retweetledi

最近看到最棒的一篇技术文章:
Draggable objects
redblobgames.com/making-of/drag…
在前端开发中,拖动(Drag)一个图层是非常常见的需求,我相信大家大部分都能写个皮毛,但是这篇文章循序渐进,从最简单的拖动,到兼容手机和 PC,再到各种 edge cases 的修复,最后再到抽象成一个 vue 的组件,我从中学习到非常多。
每一步都配有 demo,讲解的非常详细,是一篇非常好的交互式文章,如果想把拖动完全弄懂,这篇文章就足够了。

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