RAG fundamentals
Forget about Ctrl+F! 🤯 With RAG, your documents will answer your questions directly. 😎 Step-by-step tutorial with Hugging Face and ChromaDB. Unleash the power of AI (and show off to your friends)! 💪
token_hmr
AI Dockers
Hugging Face spaces allow us to run models with very simple demos, but what if the demo breaks? Or if the user deletes it? That's why I've created docker containers with some interesting spaces, to be able to use them locally, whatever happens. In fact, if you click on any project view button, it may take you to a space that doesn't work.
tooncrafter
marker_api
brushnet
ml_mgie
cosxl
zest
ani_portrait
moondream2
idm_vton
singing_songstarter
tango2
face_to_all
sadtalker
voice_craft
coqui_tts
dynamicrafter
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Conventional commits
😠 Are your commits written in alien language? 👽 Join the club! 😅 Learn Conventional Commits in Python and stop torturing your team with cryptic messages. git-changelog and commitizen will be your new best friends. 🤝
DoLa – Decoding by Contrasting Layers Improves Factuality in Large Language Models
Have you ever talked to an LLM and they answered you something that sounds like they've been drinking machine coffee all night long 😂 That's what we call a hallucination in the LLM world! But don't worry, because it's not that your language model is crazy (although it can sometimes seem that way 🤪). The truth is that LLMs can be a bit... creative when it comes to generating text. But thanks to DoLa, a method that uses contrast layers to improve the feasibility of LLMs, we can keep our language models from turning into science fiction writers 😂. In this post, I'll explain how DoLa works and show you a code example so you can better understand how to make your LLMs more reliable and less prone to making up stories. Let's save our LLMs from insanity and make them more useful! 🚀
Have you seen these projects?
Subtify
GPU monitor
Alfred
Do you want to apply AI in your project? Contact me!
Do you want to improve with these tips?
Memory Calculator
Space to calculate the memory needed to run a model
Code formatter Black
Your colleague Patric is writing code that is hard to read? Share with him this code formatter that I show you in this post! Come in and learn how to format code to make it more understandable. We are not going to solve Patric's problems, but at least you won't suffer when reading it
Declarar redes neuronales de forma clara
Declare neural networks clearly in Pytorch
Use this locally
Hugging Face spaces allow us to run models with very simple demos, but what if the demo breaks? Or if the user deletes it? That's why I've created docker containers with some interesting spaces, to be able to use them locally, whatever happens. In fact, if you click on any project view button, it may take you to a space that doesn't work.
token_hmr
tooncrafter
marker_api
Do you want to apply AI in your project? Contact me!
Do you want to train your model with these datasets?
short-jokes-dataset
Dataset with jokes in English
opus100
Dataset with translations from English to Spanish
netflix_titles
Dataset with Netflix movies and series