Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

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... show more

Avi Chawla

70,413 subscribers

15,610 views • 1 year ago •via X (Twitter)

Health & Wellness Education Science & Technology

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

Advent of Claude Day 31 - Claude Agent SDK I saved the best for last. The same agent loop, tools, and context management that power Claude Code is available as an SDK. Build agents that work like Claude Code in as little as 10 lines of code. This is just the beginning. 🎇🥂

Advent of Claude Day 31 - Claude Agent SDK I saved the best for last. The same agent loop, tools, and context management that power Claude Code is available as an SDK. Build agents that work like Claude Code in as little as 10 lines of code. This is just the beginning. 🎇🥂

Ado

100,117 views • 7 months ago

Introducing Dexter. An open source financial agent in ~200 lines of code. Think: Claude Code, but for finance. What Dexter does today: • plans tasks • runs on its own • validates its work • researches stocks It’s built with OSS tools like for managing LLMs, prompts, outputs, etc. No coding experience needed to run. Goal: build the best financial agent and share every line of code along the way. Next: evals, starting with

Introducing Dexter. An open source financial agent in ~200 lines of code. Think: Claude Code, but for finance. What Dexter does today: • plans tasks • runs on its own • validates its work • researches stocks It’s built with OSS tools like for managing LLMs, prompts, outputs, etc. No coding experience needed to run. Goal: build the best financial agent and share every line of code along the way. Next: evals, starting with

Virat Singh

317,703 views • 10 months ago

Here's the Rive source file and the code behind it. The Rive file is available on the Rive Rive Marketplace, and I'll also share the code below. Apologies in advance for the messy file structure and naming conventions. At some point I stopped naming things properly and chose chaos instead.

Here's the Rive source file and the code behind it. The Rive file is available on the Rive Rive Marketplace, and I'll also share the code below. Apologies in advance for the messy file structure and naming conventions. At some point I stopped naming things properly and chose chaos instead.

Angga Motion

57,138 views • 2 months ago

it's day 6 of sharing code + tutorials for my computer vision projects "fun with computer vision dot com" 🪬 thank you to everyone for the incredible support on my launch we're up to 126 customers now next steps: > "Floor is Lava" code + tutorial will be released this week > making more video content and cross-sharing on yt / tt / ig (thank you jack friks for the inspiration to post widely and post often) > creating more structure and engagement in our discord server

it's day 6 of sharing code + tutorials for my computer vision projects "fun with computer vision dot com" 🪬 thank you to everyone for the incredible support on my launch we're up to 126 customers now next steps: > "Floor is Lava" code + tutorial will be released this week > making more video content and cross-sharing on yt / tt / ig (thank you jack friks for the inspiration to post widely and post often) > creating more structure and engagement in our discord server

AA

224,343 views • 1 year ago

here's how the whole thing works. claude code doesn't care what's behind the API. it just sends requests and expects responses. so i pointed it at my own machine instead of anthropic's servers. llama-server runs the model locally. LiteLLM sits in between and translates the API format. claude code thinks it's talking to claude. it's talking to qwen on localhost. the setup: 2x 3090s, 38 layers on GPU, 10 on CPU. 128K context window. generation is only 7 tok/s but the tradeoff is worth it. 128K means the agent can hold an entire project in memory without losing context midtask. claude code alone loads a 17.5K token system prompt on every request. tool definitions, safety rules, agent behavior. that's your baseline before you even say hello. pushed as far as i could tonight. what surprised me most wasn't the speed. it was the iteration quality. first prompt gave me a working particle sim. second prompt, the model read its own 564 lines, understood the architecture, and added trails, explosions, gravity wells, bloom effects. no handholding. 4bit quantized. 45GB on two consumer cards. running a full coding agent autonomously. detailed article coming. full benchmarks, hardware breakdowns, engine debugging, code quality. everything from setup to what broke and why.

here's how the whole thing works. claude code doesn't care what's behind the API. it just sends requests and expects responses. so i pointed it at my own machine instead of anthropic's servers. llama-server runs the model locally. LiteLLM sits in between and translates the API format. claude code thinks it's talking to claude. it's talking to qwen on localhost. the setup: 2x 3090s, 38 layers on GPU, 10 on CPU. 128K context window. generation is only 7 tok/s but the tradeoff is worth it. 128K means the agent can hold an entire project in memory without losing context midtask. claude code alone loads a 17.5K token system prompt on every request. tool definitions, safety rules, agent behavior. that's your baseline before you even say hello. pushed as far as i could tonight. what surprised me most wasn't the speed. it was the iteration quality. first prompt gave me a working particle sim. second prompt, the model read its own 564 lines, understood the architecture, and added trails, explosions, gravity wells, bloom effects. no handholding. 4bit quantized. 45GB on two consumer cards. running a full coding agent autonomously. detailed article coming. full benchmarks, hardware breakdowns, engine debugging, code quality. everything from setup to what broke and why.

Sudo su

37,623 views • 6 months ago

Fine-tune DeepSeek-OCR on your own language! (100% local) DeepSeek-OCR is a 3B-parameter vision model that achieves 97% precision while using 10× fewer vision tokens than text-based LLMs. It handles tables, papers, and handwriting without killing your GPU or budget. Why it matters: Most vision models treat documents as massive sequences of tokens, making long-context processing expensive and slow. DeepSeek-OCR uses context optical compression to convert 2D layouts into vision tokens, enabling efficient processing of complex documents. The best part? You can easily fine-tune it for your specific use case on a single GPU. I used Unsloth to run this experiment on Persian text and saw an 88.26% improvement in character error rate. ↳ Base model: 149% character error rate (CER) ↳ Fine-tuned model: 60% CER (57% more accurate) ↳ Training time: 60 steps on a single GPU Persian was just the test case. You can swap in your own dataset for any language, document type, or specific domain you're working with. I've shared the complete guide in the next tweet - all the code, notebooks, and environment setup ready to run with a single click. Everything is 100% open-source!

Fine-tune DeepSeek-OCR on your own language! (100% local) DeepSeek-OCR is a 3B-parameter vision model that achieves 97% precision while using 10× fewer vision tokens than text-based LLMs. It handles tables, papers, and handwriting without killing your GPU or budget. Why it matters: Most vision models treat documents as massive sequences of tokens, making long-context processing expensive and slow. DeepSeek-OCR uses context optical compression to convert 2D layouts into vision tokens, enabling efficient processing of complex documents. The best part? You can easily fine-tune it for your specific use case on a single GPU. I used Unsloth to run this experiment on Persian text and saw an 88.26% improvement in character error rate. ↳ Base model: 149% character error rate (CER) ↳ Fine-tuned model: 60% CER (57% more accurate) ↳ Training time: 60 steps on a single GPU Persian was just the test case. You can swap in your own dataset for any language, document type, or specific domain you're working with. I've shared the complete guide in the next tweet - all the code, notebooks, and environment setup ready to run with a single click. Everything is 100% open-source!

Akshay 🚀

126,122 views • 9 months ago

You used to see these on the wall of every computer science lab, but I'd never written one... so I wrote one this morning! It's under 200 lines, code in the comments. And if you like these littlle code excursions, follow me, and I'll keep doing them!

You used to see these on the wall of every computer science lab, but I'd never written one... so I wrote one this morning! It's under 200 lines, code in the comments. And if you like these littlle code excursions, follow me, and I'll keep doing them!

Dave W Plummer

77,836 views • 8 months ago

Next generation flight tracking app has just dropped. It has, ADSB, ATC, ACARS, CODLC, routes, navigation charts, emergency squawk code alerts, and much more! I love this app It’s called FlightDeck. The FlightDeck team has a special promo code for all my followers: FLIGHTDECK51 There is a free three day trial and it’s only available right now for the iPhone. ✈️🤓

Next generation flight tracking app has just dropped. It has, ADSB, ATC, ACARS, CODLC, routes, navigation charts, emergency squawk code alerts, and much more! I love this app It’s called FlightDeck. The FlightDeck team has a special promo code for all my followers: FLIGHTDECK51 There is a free three day trial and it’s only available right now for the iPhone. ✈️🤓

Thenewarea51

54,200 views • 5 months ago

If you want new income streams, read this. 💰👀. Mom life leaves almost no time to make extra $$$… but I built a whole mobile app during nap time 😭💜 I just typed my idea and the AI built the entire app for me, NO CODE! If you want a side hustle, comment “build” and I’ll share what I used.

If you want new income streams, read this. 💰👀. Mom life leaves almost no time to make extra $$$… but I built a whole mobile app during nap time 😭💜 I just typed my idea and the AI built the entire app for me, NO CODE! If you want a side hustle, comment “build” and I’ll share what I used.

BadassMommy

35,518 views • 9 months ago

I finally got to shoot my Latex Misty Cosplay by water and it makes me so happy! 🥰 Please tell me you checked out the full video, and I didn't just make it for no reason?! 👀⬇️ Latex sent to me to shoot in by @catalystlatex

Sensitive content

I finally got to shoot my Latex Misty Cosplay by water and it makes me so happy! 🥰 Please tell me you checked out the full video, and I didn't just make it for no reason?! 👀⬇️ Latex sent to me to shoot in by @catalystlatex

Candy Valentina

20,497 views • 1 year ago

Just tried something cool on my own app. I let my app generate a workout for me using the new beta mode… and it actually built a solid session based on my goals. The idea is simple.. instead of guessing what to train, you hit generate and the app builds the workout for you. Still early days but I’m keen for people to test it and tell me what you think. Try it here:

Just tried something cool on my own app. I let my app generate a workout for me using the new beta mode… and it actually built a solid session based on my goals. The idea is simple.. instead of guessing what to train, you hit generate and the app builds the workout for you. Still early days but I’m keen for people to test it and tell me what you think. Try it here:

Shannon

14,459 views • 5 months ago

A few people have asked how I make these animations. The answer is it's just code and a screen recording. I’ll make little jigs like this interactive timeline to dial things in, but for me I find this is still the fastest way to create and refine exactly what I want.

A few people have asked how I make these animations. The answer is it's just code and a screen recording. I’ll make little jigs like this interactive timeline to dial things in, but for me I find this is still the fastest way to create and refine exactly what I want.

joshpuckett

53,125 views • 2 months ago

My project has 39,205 lines of code, and Cursor can't answer questions about it. Cursor's context seems to be capped at around 10,000 tokens. Unfortunately, this is not enough for any decent-sized project. If you have a large codebase, check out Augment Code. This thing is faaaast! I'm currently using their Visual Studio Code plugin, but you can also use them on JetBrains, Neovim, and even Vim. (I'm a Neovim fan, but Copilot's implementation for Neovim is nowhere as good as Augment Code.) Augment Code was gracious enough to sponsor this post. After you install their extension and run it for the first time, it will index your entire codebase. This is why it can answer questions as fast as it does, regardless of the size of your codebase. Augment Code supports chat and completions like every other AI coding assistant, but its killer feature is "Next Edit." When you make a change, two things happen: 1. The model analyzes the change to determine the ripple effects across your *entire* codebase. 2. The model suggests everything you need to update to ensure everything works correctly. This is pretty wild!

My project has 39,205 lines of code, and Cursor can't answer questions about it. Cursor's context seems to be capped at around 10,000 tokens. Unfortunately, this is not enough for any decent-sized project. If you have a large codebase, check out Augment Code. This thing is faaaast! I'm currently using their Visual Studio Code plugin, but you can also use them on JetBrains, Neovim, and even Vim. (I'm a Neovim fan, but Copilot's implementation for Neovim is nowhere as good as Augment Code.) Augment Code was gracious enough to sponsor this post. After you install their extension and run it for the first time, it will index your entire codebase. This is why it can answer questions as fast as it does, regardless of the size of your codebase. Augment Code supports chat and completions like every other AI coding assistant, but its killer feature is "Next Edit." When you make a change, two things happen: 1. The model analyzes the change to determine the ripple effects across your entire codebase. 2. The model suggests everything you need to update to ensure everything works correctly. This is pretty wild!

Santiago

247,833 views • 1 year ago

If you are using an if statement inside a for loop, did you know there's a better way of doing this is Swift? I'm talking about the where clause. Using the where clause in a for loop can provide several benefits over using an if statement inside a for loop: Readability: It explicitly states the condition that must be met for an element to be processed, making the purpose of the loop clearer to anyone reading the code. Efficiency: When using a where clause, the filtering of elements is done at the level of the sequence, which can be more efficient than filtering within the loop with an if statement. Brevity: Using a where clause often results in more concise code, as it eliminates the need for an if statement and associated braces. This can make the code more manageable and easier to maintain.

If you are using an if statement inside a for loop, did you know there's a better way of doing this is Swift? I'm talking about the where clause. Using the where clause in a for loop can provide several benefits over using an if statement inside a for loop: Readability: It explicitly states the condition that must be met for an element to be processed, making the purpose of the loop clearer to anyone reading the code. Efficiency: When using a where clause, the filtering of elements is done at the level of the sequence, which can be more efficient than filtering within the loop with an if statement. Brevity: Using a where clause often results in more concise code, as it eliminates the need for an if statement and associated braces. This can make the code more manageable and easier to maintain.

Everton Carneiro

23,416 views • 2 years ago

The future of AI in web development? This app generates code and images to convert a screenshot into HTML/Tailwind CSS. I just gave it a screenshot of my X feed, and look what it produced (Notes & link in the comments):

The future of AI in web development? This app generates code and images to convert a screenshot into HTML/Tailwind CSS. I just gave it a screenshot of my X feed, and look what it produced (Notes & link in the comments):

Alvaro Cintas

303,527 views • 2 years ago

Update: reached a milestone of 10 tutorials published on "fun with computer vision dot com" 🪬 - 185 customers - $3.9k revenue - >1 million views it's been 21 days since I launched this project, and I'm grateful for your incredible support and kindness 💗 thank you to Three.js and mediapipe for the magic behind these computer vision / augmented reality experiments this project has been incredibly fun and I have lots more I want to create more experiments - demos - tutorials - code, coming soon to a tweet near you :]

Update: reached a milestone of 10 tutorials published on "fun with computer vision dot com" 🪬 - 185 customers - $3.9k revenue - >1 million views it's been 21 days since I launched this project, and I'm grateful for your incredible support and kindness 💗 thank you to Three.js and mediapipe for the magic behind these computer vision / augmented reality experiments this project has been incredibly fun and I have lots more I want to create more experiments - demos - tutorials - code, coming soon to a tweet near you :]

AA

261,483 views • 1 year ago

Imagine you want to learn about the technology behind LLMs. You instantly get an 100 page book with chapters, content, and structure. What if you find the language too technical? You can change the prompt and the book – all 100 pages – adapts to your needs. What if you want to learn how to code models in python? You can ask for that too, and in seconds, every chapter has code examples alongside the instructional content. That’s the power of an Infinite Bookshelf. Open source, Powered by Groq Inc

Imagine you want to learn about the technology behind LLMs. You instantly get an 100 page book with chapters, content, and structure. What if you find the language too technical? You can change the prompt and the book – all 100 pages – adapts to your needs. What if you want to learn how to code models in python? You can ask for that too, and in seconds, every chapter has code examples alongside the instructional content. That’s the power of an Infinite Bookshelf. Open source, Powered by Groq Inc

Ben Klieger

62,600 views • 2 years ago