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Hack of the day: Llama on a microcontroller 🦙🔬 Details and source code at Thanks to Andrej Karpathy, whose llama2.c inspired this!

Max Braun

6,972 subscribers

463,764 次观看 • 2 年前 •via X (Twitter)

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Here are ten 42M TinyStories models running simultaneously in the browser. Andrej Karpathy's Llama2.c code has been ported to Rust using the Candle framework and compiled to Wasm.

Here are ten 42M TinyStories models running simultaneously in the browser. Andrej Karpathy's Llama2.c code has been ported to Rust using the Candle framework and compiled to Wasm.

Radamés Ajna

45,424 次观看 • 3 年前

Inspired by Andrej Karpathy and the idea of using games to compare LLMs, I've built a version of the game Codenames where different models are paired in teams to play the game with each other. Fun to see o3-mini team with R1 against Grok and Gemini! Link and repo below.

Inspired by Andrej Karpathy and the idea of using games to compare LLMs, I've built a version of the game Codenames where different models are paired in teams to play the game with each other. Fun to see o3-mini team with R1 against Grok and Gemini! Link and repo below.

Ilya Abyzov

378,880 次观看 • 1 年前

Meta just announced that Code Llama was now free for both research and commercial. This might the strongest competitor to ChatGPT: ▸ Can generate, explain, and debug your code ▸ Handles input 100,000 tokens ▸ Free for research + commercial use ▸ Outperforms most open models ▸ Comes in 7B, 13B, and 34B ▸ Supports Python, C++, Java, PHP, Typescript (Javascript), C#, and Bash Available in: ▸ Foundation base models (Code Llama) ▸ Python specializations (Code Llama - Python), ▸ Instruction-following models (Code Llama - Instruct)

Meta just announced that Code Llama was now free for both research and commercial. This might the strongest competitor to ChatGPT: ▸ Can generate, explain, and debug your code ▸ Handles input 100,000 tokens ▸ Free for research + commercial use ▸ Outperforms most open models ▸ Comes in 7B, 13B, and 34B ▸ Supports Python, C++, Java, PHP, Typescript (Javascript), C#, and Bash Available in: ▸ Foundation base models (Code Llama) ▸ Python specializations (Code Llama - Python), ▸ Instruction-following models (Code Llama - Instruct)

Lior Alexander

196,418 次观看 • 3 年前

Code LLaMA is now on Perplexity’s LLaMa Chat! Try asking it to write a function for you, or explain a code snippet: 🔗 This is the fastest way to try AI at Meta’s latest code-specialized LLM. With our model deployment expertise, we are able to provide you with this model less than 24 hours of it’s release. What’s next? We’ll integrate code LLaMA into Perplexity, all in service of providing you with the best answers to your most technical questions!

Code LLaMA is now on Perplexity’s LLaMa Chat! Try asking it to write a function for you, or explain a code snippet: 🔗 This is the fastest way to try AI at Meta’s latest code-specialized LLM. With our model deployment expertise, we are able to provide you with this model less than 24 hours of it’s release. What’s next? We’ll integrate code LLaMA into Perplexity, all in service of providing you with the best answers to your most technical questions!

Perplexity

274,613 次观看 • 3 年前

day 23 of forking Paperclip today i added knowledge bases for projects and you company. based on Andrej Karpathy idea below. added a 'system chores' and 'agent chores' to manage memory. after each heartbeat run memories get added ('agent chores') and every 4 hours memeries get managed. This is in a db with an API for all agents to use and is seperated form the agents memeroes which they get at instantiation time.

day 23 of forking Paperclip today i added knowledge bases for projects and you company. based on Andrej Karpathy idea below. added a 'system chores' and 'agent chores' to manage memory. after each heartbeat run memories get added ('agent chores') and every 4 hours memeries get managed. This is in a db with an API for all agents to use and is seperated form the agents memeroes which they get at instantiation time.

Michael Houghton 🐺

18,188 次观看 • 5 个月前

Tired of manual prompt tweaking? Watch the latest Llama tutorial on how to optimize your existing GPT or other LLM prompts for Llama with `llama-prompt-ops`, the open-source Python library! In this video, Partner Engineer Justin Lee demonstrates installation, project setup, migrating your first prompt, and analyzing performance gains. Watch now to discover: ✨ Why systematic prompt optimization is crucial for migrating from GPT to Llama. 💻 A live code walkthrough of `llama-prompt-ops` in action for a customer service classification task. Watch the full tutorial here:

Tired of manual prompt tweaking? Watch the latest Llama tutorial on how to optimize your existing GPT or other LLM prompts for Llama with `llama-prompt-ops`, the open-source Python library! In this video, Partner Engineer Justin Lee demonstrates installation, project setup, migrating your first prompt, and analyzing performance gains. Watch now to discover: ✨ Why systematic prompt optimization is crucial for migrating from GPT to Llama. 💻 A live code walkthrough of `llama-prompt-ops` in action for a customer service classification task. Watch the full tutorial here:

Meta for Developers

38,166 次观看 • 1 年前

Finally Neuraxon is out!!! Our new paper & code & demo by Jose Sánchez & David Vivancos - e/acc expanding on the Qubic #Aigarth #intelligenttissue by Come-from-Beyond the path towards #TrueAI "A New Neural Growth & Computation Blueprint" one step forward to #AGI & #ASI Read the preprint Paper: (All the details of our ongoing research) Explore the Code: (Please give us a⭐fork and build!) Play with the Interactive Demo: (Build your own Neuraxon NetWork) Andrej Karpathy do you want to give it a try? Beff (e/acc) can we try it on Extropic hw? And more to come stay tuned! #EAGI #Neuraxon #Trinarystates #Continuousprocessing #Synapticdynamics #Neuralplasticity #Spontaneousactivity #Temporalsynchronisation #Bioinspiredcomputation #Artificiology

Finally Neuraxon is out!!! Our new paper & code & demo by Jose Sánchez & David Vivancos - e/acc expanding on the Qubic #Aigarth #intelligenttissue by Come-from-Beyond the path towards #TrueAI "A New Neural Growth & Computation Blueprint" one step forward to #AGI & #ASI Read the preprint Paper: (All the details of our ongoing research) Explore the Code: (Please give us a⭐fork and build!) Play with the Interactive Demo: (Build your own Neuraxon NetWork) Andrej Karpathy do you want to give it a try? Beff (e/acc) can we try it on Extropic hw? And more to come stay tuned! #EAGI #Neuraxon #Trinarystates #Continuousprocessing #Synapticdynamics #Neuralplasticity #Spontaneousactivity #Temporalsynchronisation #Bioinspiredcomputation #Artificiology

David Vivancos - e/acc

110,424 次观看 • 10 个月前

☃️On the 19th day of #Kwikmas, Kwik Fit gifted me a an iPad thanks to our friends at Pirelli️ ☃️ Like this post and tag a friend to enter!!! T&C's

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Kwik-Fit

39,194 次观看 • 2 年前

Here’s the #Flutter implementation of this cool Airbnb interaction 🤩 The recipe is just the good old built-in #Hero widget with some 3D transform tricks 🪄! 🔗 Source code: Read on for the code details👇🏼 1/5

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Roaa 🦄💙

429,485 次观看 • 3 年前

This is WILD. Andrej Karpathy ranked every job in america by AI exposure > scraped 342 occupations from the bureau of labor statistics > used an LLM to score each job > built a treemap showing job size and AI risk main signal: fully digital work from home jobs are most exposed average score: 5.3/10 The whole thing is open source. Yeah, we’re cooked.

This is WILD. Andrej Karpathy ranked every job in america by AI exposure > scraped 342 occupations from the bureau of labor statistics > used an LLM to score each job > built a treemap showing job size and AI risk main signal: fully digital work from home jobs are most exposed average score: 5.3/10 The whole thing is open source. Yeah, we’re cooked.

CG

21,422 次观看 • 6 个月前

I just created my own LaTeX-OCR app using Llama 3.2 Vision! Upload the LaTeX code as an image, and it gives you the corresponding LaTeX code using Llama 3.2 multimodal! Here's what I used: - Ollama for serving Llama 3.2 vision locally - Streamlit for the UI Everything is just 50 lines of code! Find the code in the next tweet. -- Every day, I share tutorials and insights on DS, ML, LLMs, and RAGs. Find me → Avi Chawla

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Avi Chawla

15,628 次观看 • 1 年前

I genuinely don't understand why everyone isn't using this yet Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain. You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets. Here's the whole thing: > Install Obsidian, create a vault, open it in Claude Code > Paste Karpathy's wiki idea file and tell Claude to build it > Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it > Drop any source into raw and say "ingest this" > Ask questions across everything, forever Five minutes to set up, and you never start from a blank chat again. Full step-by-step guide with Claude and Obsidian, link below. Bookmark this

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Ridark

7,016,336 次观看 • 3 个月前

While at #OpenSourceAIWeek, Andrej Karpathy received one of our first NVIDIA DGX Sparks, personally delivered by Nader Khalil🍊 and @Baxate_carter. 🙌 Excellent work by Andrej on introducing Nanochat -- an #opensource project that makes it easy for developers to explore and train their own LLMs from scratch. We can’t wait to see what you’ll do with your Spark! #SparkSomethingBig ✨

While at #OpenSourceAIWeek, Andrej Karpathy received one of our first NVIDIA DGX Sparks, personally delivered by Nader Khalil🍊 and @Baxate_carter. 🙌 Excellent work by Andrej on introducing Nanochat -- an #opensource project that makes it easy for developers to explore and train their own LLMs from scratch. We can’t wait to see what you’ll do with your Spark! #SparkSomethingBig ✨

NVIDIA AI Developer

48,804 次观看 • 11 个月前

late to the party but built a UI layer on top of the wiki my OpenClaw🦞 agent writes and maintains, based on exactly what Andrej Karpathy describes here. obsidian vault underneath, react frontend on top: search, an interactive knowledge graph, topic browsing, article pages with tables of contents + neighborhood mini-graph and many more.

late to the party but built a UI layer on top of the wiki my OpenClaw🦞 agent writes and maintains, based on exactly what Andrej Karpathy describes here. obsidian vault underneath, react frontend on top: search, an interactive knowledge graph, topic browsing, article pages with tables of contents + neighborhood mini-graph and many more.

Ansub

111,922 次观看 • 5 个月前

Introducing LLaMa Chat: The fastest way to chat with AI at Meta/Meta's Llama2! Try it here: feedback appreciated! This is our first step towards building a blazing-fast LLM inference completely in-house, for everyone to try. What's next? We'll be hooking up the bigger LLAMAs and eventually deploying our own in-house LLMs. All of this in service of building the best and fastest answer engine. Come join us, we're hiring!

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🔍 Code Decompiler arrives on #SuiVision! Our commitment to transparency for developers and users just got stronger. It brings Sui Code transparent by converting bytecode into readable source code. Special thanks to Sam Blackshear for the insights and step-by-step guides. 🌟 Watch the video for the full scoop!

🔍 Code Decompiler arrives on #SuiVision! Our commitment to transparency for developers and users just got stronger. It brings Sui Code transparent by converting bytecode into readable source code. Special thanks to Sam Blackshear for the insights and step-by-step guides. 🌟 Watch the video for the full scoop!

BlockVision

44,734 次观看 • 2 年前

Next time you want to throw your Dhaniya roots away, think again. Sister shows a beautiful hack to grow unlimited Coriander at home ❤️❤️❤️ Hack of the day. #FI

Next time you want to throw your Dhaniya roots away, think again. Sister shows a beautiful hack to grow unlimited Coriander at home ❤️❤️❤️ Hack of the day. #FI

Fundamental Investor ™ 🇮🇳

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This was us haha. Sreejith PP Arpit Saxena and I built Andrej Karpathy-fy! It takes a paperswithcode link, your current proficiency and gives you a tailored 5 lesson plan to go from where you are to the meaty parts of the paper implementation - like the karpathy video series / labml style. This is a task none of the previous models could do, and O1 was really good at. The best part? The output is an executable ipynb notebook (which you can use minusxai to work through :) ) The below video has apple's recent monocular depth paper. I could actually go through and understand it, with loss functions from the paper and everything!

This was us haha. Sreejith PP Arpit Saxena and I built Andrej Karpathy-fy! It takes a paperswithcode link, your current proficiency and gives you a tailored 5 lesson plan to go from where you are to the meaty parts of the paper implementation - like the karpathy video series / labml style. This is a task none of the previous models could do, and O1 was really good at. The best part? The output is an executable ipynb notebook (which you can use minusxai to work through :) ) The below video has apple's recent monocular depth paper. I could actually go through and understand it, with loss functions from the paper and everything!

Vivek Aithal

200,848 次观看 • 1 年前