Sébastien

Software Engineer who has a passion for UX, DX and Architecture

[Sébastien @demsking]

Hey @VueToolbox, @vuejsdevelopers, @vuejsfeed, @VueVixens, @VueNewsletter, @elevatebart, I just release Vuedoc 4.0.0 Beta, a major release which adds support of Vue 3 and Composition API #VueJS 🥳

NPM:
- https://t.co/vier2ManAl
- https://t.co/l8FWSN2bSN

[Akshay 🚀 @akshay_pachaar]

Microsoft just changed the game! 🔥

They've open-sourced bitnet.cpp: a blazing-fast 1-bit LLM inference framework that runs directly on CPUs.

Why is this a game-changer❓

You can now run 100B parameter models on local devices with up to 6x speed improvements and 82% less energy consumption—all without a GPU!

The future we've been waiting for: fast, efficient, and private AI that works anytime, anywhere.✨

Link to the GitHub repo in next tweet!
_____
Find me → @akshay_pachaar ✔️
For more insights and tutorials on AI and Machine Learning!

[LEERON @leeron]

Evaluating the Openness of Open Source AI Models

Many AI models claim to be open but restrict code & data access.

Companies like Meta & Microsoft label their models open but share little info. This practice, called open-washing, fakes transparency.

Truly open models should let researchers replicate and examine them, which isn't always true.

#open #ai #genai #llm #meta #microsoft #chatglm #mistral #qwen #mixtral #falcon #commandr #gemma #llama #chatgpt

[Thor 雷神 ⚡️ @thorwebdev]

If you love Maps you will love @protomaps! It's an open source map of the world, deployable as a single static file on @supabase Storage! 🗺️

Lots of cool stuff we can do, but let's get started with the basics, serving map tiles from storage and rendering with @maplibre 📍

[Holden @hodlenx]

🚀 Excited to introduce PowerInfer-2: A game-changing LLM inference engine for mobile devices by the #PowerInfer team. It smoothly runs a 47B model with a staggering 29x speedup on smartphones! Watch our demo to see it in action! 🎥
Technical details at: https://t.co/7bx5EnzWCs

[Neo Kim @systemdesignone]

If you want to become better at system design, learn these case studies:

[bearstech @bearstech]

Vous manquez de RAM ? Téléchargez-la ! (lu)
https://t.co/FViBtmjEll

[Virat Singh @virattt]

I finally understand how GPT generates text.

Really helps to code it from scratch in Python.

There are 5 components:
• token embeddings
• positional embeddings
• transformer blocks
• layer normalization
• output head

It sounds complex, but grokking GPT is simple.

Token embeddings turn input text into meaningful vectors that capture semantic meaning.

Positional embeddings encode positions of input tokens. This tells GPT "where" each token is in the input text.

Transformer blocks are the processing powerhouse. This is where attention and training happens.

Layer normalization smooths out the data, which enhances training stability.

Output head translates the learned features into a next token prediction.

And that's it!

I recommend running the code below and then implementing it step-by-step on your own.

Happy learning.

[LAION @laion_ai]

Help us build an open GPT-4-Omni! With this blog post we show promising directions (including data sets and tutorials)
https://t.co/bm7y2ZboL4

[ollama @ollama]

ollama run codestral

https://t.co/DyBxEXVUPc

[bearstech @bearstech]

Univer : une alternative Open Source à Google Sheets, Slides et Docs. Il se veut flexible et modulaire. Il permet notamment l'intégration de documents dans vos applications via des embeds et met l'accent sur la performance.
https://t.co/DACMzjdzJE

[Ashpreet Bedi @ashpreetbedi]

Mind blowing 🤯 function calling by the new `Hermes 2 on Llama-3` by @teknium @intrstllrninja running on @ollama

The last question asks it to do 3 different function calls and write an article. Just check that quality.

code: https://t.co/QLscvoY45i

[Luis Catacora @lucataco]

llama-3-vision-alpha running on @replicate

I got it up before the HF version was pushed out 😅

Try it out!👇

[Vaibhav (VB) Srivastav @reach_vb]

Let's go!! Common Voice 17 - now on the Hub! 🔥

With 31,000 hours of audio (& transcriptions) across 124 languages.

*sound on 🎶*

847 hours of data were added in CV 17, along with 493 hours of validated data.

Four new languages have been added to this edition: Haitian Creole, Nso, Zulu, and Zaza. Making CV 17 even more powerful.

NEW: we'll also added a new split, `validated.` This should seriously increase the amount of data available for your downstream tasks.

Want to use it?

from datasets import load_dataset

cv17 = load_dataset("mozilla-foundation/common_voice_17_0",
"hi",
split="test",
streaming=True)

[Sébastien @demsking]

@DidierGirard Je l'utilise depuis 1 semaine et je gagne en productivité 😁😋

[DidierGirard［Ξ］🏃🐝🐦 ⚛️ @DidierGirard]

Quelqu'un connait ? Utilise ? https://t.co/MV7avVnsHJ

[Shruti @heyshrutimishra]

NVIDIA just released FREE online courses in AI.

Here are 9 courses you can't afford to miss:

[pilcrow @pilcrowonpaper]

Announcing the Copenhagen Book - an open source guide on implementing auth for the web! It covers everything, including sessions, CSRF protection, passkeys, OAuth, 2FA, email verification, and password reset
https://t.co/F0CcuqQ4yH

[Google for Developers @googledevs]

📢 Announcing the MediaPipe LLM Inference API → https://t.co/TvaugBiCBn

Learn to run Gemma & other on-device LLMs with MediaPipe & @TensorFlow Lite, & get updates on:

💡 Performance & optimizations
🛠️ Supported model architectures
🧠 Experimental LLM Inference API
🧡 & more!

[Linux Format @linuxformat]

Run your own private ChatGPT.

https://t.co/2Q0aWuH5sT

[Open Web Advocacy @OpenWebAdvocacy]

Let’s make it very clear. Apple is under NO obligation to kill Web Apps in the EU. It’s a spiteful decision driven from pure greed.

Don’t put up with it, join us in fighting back

https://t.co/kp050QgqYb