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Code for 1st place solution to Kaggle's Abstraction and Reasoning Challenge
Abstract Reasoning with Graph Abstractions (ARGA) implementation
A deep dive into embeddings starting from fundamentals
Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting
Plain python implementations of basic machine learning algorithms
code for CVPR2024 paper: DiffMOT: A Real-time Diffusion-based Multiple Object Tracker with Non-linear Prediction
The official PyTorch implementation of Google's Gemma models
We write your reusable computer vision tools. 💜
Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristi…
A recommender system for Wikipedia pages.
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
A list of blogs, videos, and other content that provides advice on building experimentation and A/B testing platforms
Python class to scrape data from rightmove.co.uk and return listings in a pandas DataFrame object
A collection of stand-alone Python machine learning recipes
Bayesian Modeling and Probabilistic Programming in Python
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Official implementation of our NeurIPS 2023 paper "Augmenting Language Models with Long-Term Memory".
📋 A list of open LLMs available for commercial use.
PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The most effective open source solution to turn your pdf files in a chatbot!
A pure-python PDF library capable of splitting, merging, cropping, and transforming the pages of PDF files
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
A generative AI extension for JupyterLab
Publication-ready NN-architecture schematics.
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.