Popular GitHub Repositories for Mean Average Precision

StarVector is a foundation model for SVG generation that transforms vectorization into a code generation task. Using a vision-language modeling architecture, StarVector processes both visual and textual inputs to produce high-quality SVG code with remarkable precision.

Control GenAI interactions with power, precision, and consistency using LLM-native Conversation Design paradigms

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

Build, customize and control you own LLMs. From data pre-processing to fine-tuning, xTuring provides an easy way to personalize open-source LLMs. Join our discord community: https://discord.gg/TgHXuSJEk6

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference.

Toolkit for efficient experimentation with Speech Recognition, Text2Speech and NLP

A collaboratively written review paper on deep learning, genomics, and precision medicine

Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.

High-fidelity performance metrics for generative models in PyTorch

Neural Network Compression Framework for enhanced OpenVINO? inference

Simple and Efficient Tensorflow implementations of NER models with tf.estimator and tf.data

A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.

[ICLR 2025] Official implementation of Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration

Pytorch Implementation (unofficial) of the paper "Mean Flows for One-step Generative Modeling" by Geng et al.

Microsoft Automatic Mixed Precision Library

OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network

Precision Medicine Knowledge Graph (PrimeKG)

To learn and reason like humans, AI must first learn to factorise interpretable representations of independent data generative factors (preferably in an unsupervised manner!!). What does all this mean? Go through this tutorial to get an overview of disentanglement in the context of unsupervised visual disentangled representation learning.

Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2/Keras. For speech enhancement and robust ASR.

TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools