4 个仓库
Awesome GitHub RepositoriesTest Set Inference Evaluators
Runs a trained model on held-out data and computes performance metrics to measure accuracy.
Distinct from Model Testing: Distinct from Model Testing: focuses specifically on inference on held-out test sets rather than broader model testing methodologies.
Explore 4 awesome GitHub repositories matching testing & quality assurance · Test Set Inference Evaluators. Refine with filters or upvote what's useful.
Awesome Test Set Inference Evaluators GitHub Repositories
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- diegosouzapw/omniroute
diegosouzapw/OmniRoute
6,391在 GitHub 上查看OmniRoute is a unified LLM API gateway that connects multiple AI providers to a single endpoint. Its primary purpose is to simplify the integration of various AI models into tools and agents by translating different provider formats into a standardized API. The project distinguishes itself through a multi-strategy request routing system that optimizes for cost, speed, and availability, including automatic model fallbacks and a circuit-breaker resilience model to isolate provider failures. It employs a local-first security posture, using AES-256-GCM encryption to store API keys and conversatio
Includes tools to score model responses against golden test sets using regex, exact match, or custom criteria.
TypeScript - biolab/orange3
biolab/orange3
5,635在 GitHub 上查看Orange3 is a visual data mining platform that provides an interactive canvas for building data analysis workflows without writing code. At its core, it offers a widget-based visual programming environment where users connect configurable components to perform data preprocessing, machine learning model training, statistical evaluation, and interactive visualization. The platform is built on NumPy-backed data tables with domain descriptors that define variable names, types, and roles, and includes a lazy SQL query proxy for working with database tables without loading all data into memory. The
Applies trained models to independent datasets to estimate performance on unseen data.
Python - microsoft/biogpt
microsoft/BioGPT
4,486在 GitHub 上查看BioGPT is a biomedical large language model and domain-specific transformer designed for processing and creating specialized medical text. It functions as a generative tool and knowledge extraction engine trained on large-scale scientific literature to produce human-like scientific prose and factual responses to queries. The project provides specialized capabilities for biomedical named entity recognition and the extraction of complex relations from unstructured medical corpora. It is designed to identify and classify biological entities through data mining and relation extraction to support
Runs trained models on held-out data and computes performance metrics to measure accuracy.
Python - cs230-stanford/cs230-code-examples
cs230-stanford/cs230-code-examples
4,218在 GitHub 上查看This repository provides structured code examples and project templates designed for classroom instruction in machine learning and neural networks. It offers reference implementations of deep learning models for both computer vision and natural language processing tasks, built using PyTorch as the core framework. The codebase is organized as a modular project template with separate directories for data handling, model definitions, and training scripts, promoting reusability and clarity. It includes predefined pipelines for image classification and text processing, along with a command-line in
Includes a separate script to compute accuracy and loss on held-out test data after training.
Pythoncomputer-visionnatural-language-processingpytorch
