Popular GitHub Repositories for Compare Scores

Test your prompts, agents, and RAGs. Red teaming, pentesting, and vulnerability scanning for LLMs. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and CI/CD integration.

Keras Attention Layer (Luong and Bahdanau scores).

similarity: Text similarity calculation Toolkit for Java. 文本相似度计算工具包，java编写，可用于文本相似度计算、情感分析等任务，开箱即用。

Compare the performance of different LLM that can be deployed locally on consumer hardware. Run yourself with Colab WebUI.

A multi-platform desktop application to evaluate and compare LLM models, written in Rust and React.

The 100 line AI agent that solves GitHub issues or helps you in your command line. Radically simple, no crazy configs, no giant monorepo—but scores 65% on SWE-bench verified!

Face recognition SDK Android with 3D passive face liveness detection: face recognition by face matching, face compare, face comparison, face identification, face anti-spoofing, face identity, facial recognition, face representation, face reconstruction, and face liveness detection for IDV

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

Compare SELUs (scaled exponential linear units) with other activations on MNIST, CIFAR10, etc.

Compare neural networks by their feature similarity

NIST_FRVT Top 1? Face Recognition, Liveness Detection(Face Anti-Spoof), Face Attribute Analysis Linux Server SDK Demo ?? Face Recognition ?? Face Matching ?? Face Liveness Detection ?? Face Identification (1:N Face Search) ?? Face Attribute Analysis

Enabling easy statistical significance testing for deep neural networks.

Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].

Vector AI — A platform for building vector based applications. Encode, query and analyse data using vectors.

Dataset and code of GTSinger(NeurIPS 2024 Spotlight): A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks

In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.

3D Passive Face Liveness Detection (Anti-Spoofing) & Deepfake detection. A single image is needed to compute liveness score. 99,67% accuracy on our dataset and perfect scores on multiple public datasets (NUAA, CASIA FASD, MSU...).

Neat (Neural Attention) Vision, is a visualization tool for the attention mechanisms of deep-learning models for Natural Language Processing (NLP) tasks. (framework-agnostic)

Face recognition Flutter SDK with 3D passive face liveness detection: face matching, face compare, face comparison, face identification, face anti-spoofing, face identity, facial recognition, face representation, face reconstruction, face tracking, and face liveness detection for IDV

Python based Graph Propagation algorithm, DeepWalk to evaluate and compare preference propagation algorithms in heterogeneous information networks from user item relation ship.