Search Results for "test" - Page 13
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Showing 324 open source projects for "test"
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This software is a Library for Adaptive Boosting (AdaBoost). It provides a generic framework for the study of the Boosting algorithms. The framework provides the different tasks for boosting: Learning, Validation, Test, Profiling and Performance Analysis
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"Java Artificial Intelligence Markup Language PAD" is a tool that manages ProgramD AI (on local or remote machines) and AIML files with real-time previews and it provides a network support to test AI capabilities over many network protocols.
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JAgent is a multi-agents system test and development platform. It provides a framework and GUIs helping to create and test collective strategies in a multi-agents system.
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CRFChunker: Conditional Random Fields Phrase Chunker (Phrase Chunking Tool) for English. The model was trained on sections 01..24 of WSJ corpus and using section 00 as the development test set (F1-score of 95.77). Chunking speed: 700 sentences/s
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Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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CRFTagger: Conditional Random Fields Part-of-Speech (POS) Tagger for English. The model was trained on sections 01..24 of WSJ corpus and using section 00 as the development test set (accuracy of 97.00%). Tagging speed: 500 sentences/s.
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...The container simulates an environment, and gives to the robots living in it access to sensor views. The goal of this project is to provide the open source community a tool for robot behavior test and challeng
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AI-TEM is a Artificial Intelligence (AI) testbed made by game console emulator. User , developer or researcher can implement many AI and test it on real commercial game. (Suitable emulator and ROM required, see more detail inside...).
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DAI = Distributed Artificial Intelligence The projected is intended to be a test bed for AI related concepts and technologies, not necessarily an end user product, though that could change. Some of the modules can be modified for other uses.
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This package contains code for the game of EasyGo, a modified version of the original game of go. This package provides a simple API so that the users can code and test their own players. Thus one can not only play, but also program their own players.
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Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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Yawn: Yet Another W* Network: a java framework for developing, training and testing neural networks independently of the model and test environment.
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EBBA is a project aiming to develop an advanced chatbot by combining AIML, 3d facial expressions, speech synthesizer, speech recognition and an iq-test solving functionality.
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Unit tests-based Genetic Programming in Java. The developer specifies unit tests, and the tool will use GP to evolve software that passes those tests.
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A complete C++ library to design, construct and test connectionist systems based on neural networks. Requires VDK library
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AI Now is an open source endeavour to create a general purpose Artificial Intelligence. The plan is to implement a modular architecture to incorporate AI theories as they are developed. This will provide a growing platform to test new AI theories.
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OpenAI Realtime Console
React app for inspecting, building and debugging with the Realtime API
...This console serves as a reference implementation, showing how to establish WebRTC or WebSocket connections, send audio or text inputs, and receive model outputs in real time. It is built as a simple frontend that developers can run locally to test and understand how Realtime API interactions work. The project is intended as an educational and debugging resource rather than a production-ready application. By offering clear examples of streaming inputs and outputs, the console helps developers accelerate prototyping of real-time AI-powered applications. -
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k-Nearest Neighbors (kNN) - MATLAB
Complete package
Function 1. classifier_knn 2. accuracy_knn Description 1. Returns the estimated label of one test instance, the k nearest training instances, the k nearest training labels and creates a chart circulating the nearest training instances (chart 2-D of the first two features of each instance). 2. Returns the estimated labels of one or multiple test instances and the accuracy of the estimates. -
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3A-TRE
3A-TRE evaluates traditionally logical expressions under 3 assumptions
...The closed world assumption (CWA) is the assumption that any statement that is not known to be true is false. We distinguish yet another case in software testing. Frequently, there are test stubs which simulate the behaviors of the dependent test modules. In this case, the dependent test modules are always assumed to be true when their results are not available. We call this a stub assumption (SA). 3A-TRE example: echo "CWA: (T and U)" | java -jar PTRE.jar Result: F 3A-PTRE example: (P means possible results) echo "OWA: (T,U and U,F)" | java -jar PTRE.jar Result: U,F -
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lastest
AI-supported visual verification and tests you can actually trust.
...An AI agent records you clicking through your running app and generates Playwright tests with multi-selector fallback. Replays are deterministic and token-free, so your CI/CD bill doesn't scale with your test suite. Lastest ships three diff engines side-by-side — pixel (pixelmatch), structural (SSIM), and perceptual (Butteraugli) — so flaky pixel diffs stop crying wolf. A review dashboard tracks baselines, approvals, and audit history. Run it via Docker on your own infrastructure for unlimited screenshots and full data residency, or run on Lastest Cloud for managed CI runners. ... -
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In this project we develop algorithms that can solve a cooperative problem between four agent types, and their goal is to repair a surface time-efficiently, and a multi-agent simulator application to parametrize, animate, and test the solution.
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It's an implementation of the A* algorithm together with a grid processor which pre-processes 8-bit bpm graphic files using a variable resolution and an SDL user interface to test it.
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videonetwork
A simulator for self-organizing video replication and more
...The transport path of content is exploited to replicate content and limited storage space is handled by clean-up mechanisms. We implemented a simulator to show the algorithm's performance and to test its behavior under real circumstances. It is easily extendable to support several new scenarios or changes to the algorithm (see replication and client models). -
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ZAYA1-8B
Efficient MoE reasoning model for coding and math workloads
...The model contains 8.4B total parameters with around 760M active during inference, allowing it to achieve strong reasoning, mathematics, and coding performance while remaining lightweight enough for efficient local or on-device deployment. ZAYA1-8B is optimized for long-form reasoning and test-time compute workflows, making it particularly effective for mathematical problem solving, coding tasks, and advanced reasoning chains. It introduces architectural innovations such as Compressed Convolutional Attention, a novel MLP-based expert router, and learned residual scaling to improve routing stability and inference efficiency. ... -
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wav2vec2-large-xlsr-53-portuguese
Portuguese ASR model fine-tuned on XLSR-53 for 16kHz audio input
...The model performs well without a language model, though adding one can improve word error rate (WER) and character error rate (CER). It achieves a WER of 11.3% (or 9.01% with LM) on Common Voice test data, demonstrating high accuracy for a single-language ASR model. Inference can be done using HuggingSound or via a custom PyTorch script using Hugging Face Transformers and Librosa. Training scripts and evaluation methods are open source and available on GitHub. It is released under the Apache 2.0 license and intended for ASR tasks in Brazilian Portuguese. -
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wav2vec2-large-xlsr-53-russian
Russian ASR model fine-tuned on Common Voice and CSS10 datasets
...The model operates best with audio sampled at 16kHz and can transcribe Russian speech directly without a language model. It achieves a Word Error Rate (WER) of 13.3% and Character Error Rate (CER) of 2.88% on the Common Voice test set, with even better results when used with a language model. The model supports both PyTorch and JAX and is compatible with the Hugging Face Transformers and HuggingSound libraries. It is ideal for Russian voice transcription tasks in research, accessibility, and interface development. The training was made possible with compute support from OVHcloud, and the training scripts are publicly available for replication.
