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Code for paper "Patch-Level Training for Large Language Models"
Scoring rules like the Brier Score (Mean Squared Error, Quadratic Score) and Log Loss (Cross-Entropy, Negative Log-Likelihood, Logarithmic Score) can favor incorrect predictions. To address this li…
FULL v0, Cursor, Manus, Same.dev, Lovable, Devin, Replit Agent, Windsurf Agent, VSCode Agent, Dia Browser & Trae AI (And other Open Sourced) System Prompts, Tools & AI Models.
Foundational Models for State-of-the-Art Speech and Text Translation
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a neural network.
✨✨Latest Advances on Multimodal Large Language Models
A library for advanced large language model reasoning
This project focuses on designing a digital voice assistant for vehicle command recognition. This system leverages three key techniques: speech-to-text conversion using Vosk, a lightweight LLM mode…
An easy-to-use interface for measuring uncertainty and robustness.
Causal Inference and Discovery in Python by Packt Publishing
Label Studio is a multi-type data labeling and annotation tool with standardized output format
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.
[CVPR 2021] Official PyTorch Code of GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection
PyTorch Tutorial for Deep Learning Researchers
Master the fundamentals of machine learning, deep learning, and mathematical optimization by building key concepts and models from scratch using Python.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
A Survey and Taxonomy of the Recent GANs Development，computer vision & time series