Best AI tools for< Run Model Tests >

Langtail is a platform that helps developers build, test, and deploy AI-powered applications. It provides a suite of tools to help developers debug prompts, run tests, and monitor the performance of their AI models. Langtail also offers a community forum where developers can share tips and tricks, and get help from other users.

Robin by Mobile.dev is an AI-powered mobile app testing tool that allows users to test their mobile apps with confidence. It offers a simple yet powerful open-source framework called Maestro for testing mobile apps at high speed. With intuitive and reliable testing powered by AI, users can write rock-solid tests without extensive coding knowledge. Robin provides an end-to-end testing strategy, rapid testing across various devices and operating systems, and auto-healing of test flows using state-of-the-art AI models.

PromptPoint Playground is an AI tool designed to help users design, test, and deploy prompts quickly and efficiently. It enables teams to create high-quality LLM outputs through automatic testing and evaluation. The platform allows users to make non-deterministic prompts predictable, organize prompt configurations, run automated tests, and monitor usage. With a focus on collaboration and accessibility, PromptPoint Playground empowers both technical and non-technical users to leverage the power of large language models for prompt engineering.

Lumora is an AI tool designed to help users efficiently manage, optimize, and test prompts for various AI platforms. It offers features such as prompt organization, enhancement, testing, and development. Lumora aims to improve prompt outcomes and streamline prompt management for teams, providing a user-friendly interface and a playground for experimentation. The tool also integrates with various AI models for text, image, and video generation, allowing users to optimize prompts for better results.

MacWhisper is a native macOS application that utilizes OpenAI's Whisper technology for transcribing audio files into text. It offers a user-friendly interface for recording, transcribing, and editing audio, making it suitable for various use cases such as transcribing meetings, lectures, interviews, and podcasts. The application is designed to protect user privacy by performing all transcriptions locally on the device, ensuring that no data leaves the user's machine.

Cerebium is a serverless AI infrastructure platform that allows teams to build, test, and deploy AI applications quickly and efficiently. With a focus on speed, performance, and cost optimization, Cerebium offers a range of features and tools to simplify the development and deployment of AI projects. The platform ensures high reliability, security, and compliance while providing real-time logging, cost tracking, and observability tools. Cerebium also offers GPU variety and effortless autoscaling to meet the diverse needs of developers and businesses.

QuarkIQL is a generative testing tool for computer vision APIs. It allows users to create custom test images and requests with just a few clicks. QuarkIQL also provides a log of your queries so you can run more experiments without starting from square one.

Nerdynav is a website that provides reviews of AI tools and software for businesses. The website is run by Nav, a software developer and online entrepreneur who has tested over 100 tools to help businesses find the best solutions for their needs. Nerdynav's reviews are data-backed and provide insights into the features, advantages, and disadvantages of each tool. The website also includes articles on how to use AI to improve business processes and increase productivity.

Captur is an AI-powered platform that enables users to automate manual image review workflows with easy-to-use APIs. The platform offers real-time guidance to improve user experience, provides AI models for various checks, and helps transform operations for enterprises. Captur's edge AI platform allows developers, product owners, and operations teams to build, test, deploy, and iterate AI models efficiently. The platform is designed to run on-device, ensuring real-time intelligence without lag or weak signals. Captur is a comprehensive solution for deploying edge AI into real-world operations, offering features such as live guidance, quick scanning, confidence-building, and privacy verification.

Lunary is an AI developer platform designed to bring AI applications to production. It offers a comprehensive set of tools to manage, improve, and protect LLM apps. With features like Logs, Metrics, Prompts, Evaluations, and Threads, Lunary empowers users to monitor and optimize their AI agents effectively. The platform supports tasks such as tracing errors, labeling data for fine-tuning, optimizing costs, running benchmarks, and testing open-source models. Lunary also facilitates collaboration with non-technical teammates through features like A/B testing, versioning, and clean source-code management.

Dot is a free, locally-run language model that allows users to interact with their own documents, chat with the model, and use the model for a variety of tasks, all without sending their data away. It is powered by the Mistral 7B LLM, which means it can run locally on a user's device and does not give away any of their data. Dot can also run offline.

Stablematic is a web-based platform that allows users to run Stable Diffusion and other machine learning models without the need for local setup or hardware limitations. It provides a user-friendly interface, pre-installed plugins, and dedicated GPU resources for a seamless and efficient workflow. Users can generate images and videos from text prompts, merge multiple models, train custom models, and access a range of pre-trained models, including Dreambooth and CivitAi models. Stablematic also offers API access for developers and dedicated support for users to explore and utilize the capabilities of Stable Diffusion and other machine learning models.

Cascadeur is a standalone 3D software that lets you create keyframe animation, as well as clean up and edit any imported ones. Thanks to its AI-assisted and physics tools you can dramatically speed up the animation process and get high quality results. It works with .FBX, .DAE and .USD files making it easy to integrate into any animation workflow.

LM Studio is an AI tool designed for discovering, downloading, and running local LLMs (Large Language Models). Users can run LLMs on their laptops offline, use models through an in-app Chat UI or a local server, download compatible model files from HuggingFace repositories, and discover new LLMs. The tool ensures privacy by not collecting data or monitoring user actions, making it suitable for personal and business use. LM Studio supports various models like ggml Llama, MPT, and StarCoder on Hugging Face, with minimum hardware/software requirements specified for different platforms.

Together AI is an AI tool that offers a variety of generative AI services, including serverless models, fine-tuning capabilities, dedicated endpoints, and GPU clusters. Users can run or fine-tune leading open source models with only a few lines of code. The platform provides a range of functionalities for tasks such as chat, vision, text-to-speech, code/language reranking, and more. Together AI aims to simplify the process of utilizing AI models for various applications.

Subbly is a subscription-first commerce platform that provides businesses with everything they need to launch and manage a successful subscription business. With Subbly, businesses can build a website, create and manage subscriptions, process payments, and track customer data. Subbly also offers a range of features to help businesses grow their subscription revenue, including AI-powered churn prediction, customizable checkout and upsell funnels, and powerful marketing tools.

UbiOps is an AI infrastructure platform that helps teams quickly run their AI & ML workloads as reliable and secure microservices. It offers powerful AI model serving and orchestration with unmatched simplicity, speed, and scale. UbiOps allows users to deploy models and functions in minutes, manage AI workloads from a single control plane, integrate easily with tools like PyTorch and TensorFlow, and ensure security and compliance by design. The platform supports hybrid and multi-cloud workload orchestration, rapid adaptive scaling, and modular applications with unique workflow management system.

Moshi AI by Kyutai is an advanced native speech AI model that enables natural, expressive conversations. It can be installed locally and run offline, making it suitable for integration into smart home appliances and other local applications. The model, named Helium, has 7 billion parameters and is trained on text and audio codecs. Moshi AI supports native speech input and output, allowing for smooth communication with the AI. The application is community-supported, with plans for continuous improvement and adaptation.

Mystic.ai is an AI tool designed to deploy and scale Machine Learning models with ease. It offers a fully managed Kubernetes platform that runs in your own cloud, allowing users to deploy ML models in their own Azure/AWS/GCP account or in a shared GPU cluster. Mystic.ai provides cost optimizations, fast inference, simpler developer experience, and performance optimizations to ensure high-performance AI model serving. With features like pay-as-you-go API, cloud integration with AWS/Azure/GCP, and a beautiful dashboard, Mystic.ai simplifies the deployment and management of ML models for data scientists and AI engineers.

Sink In is a cloud-based platform that provides access to Stable Diffusion AI image generation models. It offers a variety of models to choose from, including majicMIX realistic, MeinaHentai, AbsoluteReality, DreamShaper, and more. Users can generate images by inputting text prompts and selecting the desired model. Sink In charges $0.0015 for each 512x512 image generated, and it offers a 99.9% reliability guarantee for images generated in the last 30 days.

The Intel® Geti™ SDK is a python package that enables teams to rapidly develop AI models by easing the complexities of model development and enhancing collaboration between teams. It provides tools to interact with an Intel® Geti™ server via the REST API, allowing for project creation, downloading, uploading, deploying for local inference with OpenVINO, setting project and model configuration, launching and monitoring training jobs, and media upload and prediction. The SDK also includes tutorial-style Jupyter notebooks demonstrating its usage.

Bugbug is a tool developed by Mozilla that leverages machine learning techniques to assist with bug and quality management, as well as other software engineering tasks like test selection and defect prediction. It provides various classifiers to suggest assignees, detect patches likely to be backed-out, classify bugs, assign product/components, distinguish between bugs and feature requests, detect bugs needing documentation, identify invalid issues, verify bugs needing QA, detect regressions, select relevant tests, track bugs, and more. Bugbug can be trained and tested using Python scripts, and it offers the ability to run model training tasks on Taskcluster. The project structure includes modules for data mining, bug/commit feature extraction, model implementations, NLP utilities, label handling, bug history playback, and GitHub issue retrieval.

This repository contains inference speed tests on Local Large Language Models on various devices. It provides results for different models tested on Macbook Pro and Mac Studio. Users can contribute their own results by running models with the provided prompt and adding the tokens-per-second output. Note that the results are not verified.

DevQualityEval is an evaluation benchmark and framework designed to compare and improve the quality of code generation of Language Model Models (LLMs). It provides developers with a standardized benchmark to enhance real-world usage in software development and offers users metrics and comparisons to assess the usefulness of LLMs for their tasks. The tool evaluates LLMs' performance in solving software development tasks and measures the quality of their results through a point-based system. Users can run specific tasks, such as test generation, across different programming languages to evaluate LLMs' language understanding and code generation capabilities.

1.5-Pints is a repository that provides a recipe to pre-train models in 9 days, aiming to create AI assistants comparable to Apple OpenELM and Microsoft Phi. It includes model architecture, training scripts, and utilities for 1.5-Pints and 0.12-Pint developed by Pints.AI. The initiative encourages replication, experimentation, and open-source development of Pint by sharing the model's codebase and architecture. The repository offers installation instructions, dataset preparation scripts, model training guidelines, and tools for model evaluation and usage. Users can also find information on finetuning models, converting lit models to HuggingFace models, and running Direct Preference Optimization (DPO) post-finetuning. Additionally, the repository includes tests to ensure code modifications do not disrupt the existing functionality.

Mistral Inference repository contains minimal code to run 7B, 8x7B, and 8x22B models. It provides model download links, installation instructions, and usage guidelines for running models via CLI or Python. The repository also includes information on guardrailing, model platforms, deployment, and references. Users can interact with models through commands like mistral-demo, mistral-chat, and mistral-common. Mistral AI models support function calling and chat interactions for tasks like testing models, chatting with models, and using Codestral as a coding assistant. The repository offers detailed documentation and links to blogs for further information.

LLM-ollama is a plugin that provides access to models running on an Ollama server. It allows users to query the Ollama server for a list of models, register them with LLM, and use them for prompting, chatting, and embedding. The plugin supports image attachments, embeddings, JSON schemas, async models, model aliases, and model options. Users can interact with Ollama models through the plugin in a seamless and efficient manner.

Yet Another Applied LLM Benchmark is a collection of diverse tests designed to evaluate the capabilities of language models in performing real-world tasks. The benchmark includes tests such as converting code, decompiling bytecode, explaining minified JavaScript, identifying encoding formats, writing parsers, and generating SQL queries. It features a dataflow domain-specific language for easily adding new tests and has nearly 100 tests based on actual scenarios encountered when working with language models. The benchmark aims to assess whether models can effectively handle tasks that users genuinely care about.

ENOVA is an open-source service for Large Language Model (LLM) deployment, monitoring, injection, and auto-scaling. It addresses challenges in deploying stable serverless LLM services on GPU clusters with auto-scaling by deconstructing the LLM service execution process and providing configuration recommendations and performance detection. Users can build and deploy LLM with few command lines, recommend optimal computing resources, experience LLM performance, observe operating status, achieve load balancing, and more. ENOVA ensures stable operation, cost-effectiveness, efficiency, and strong scalability of LLM services.

A Python package that helps Data and Analytics engineers render dbt projects in Apache Airflow DAGs. It enables teams to automatically render their dbt projects in a granular level, creating individual Airflow tasks for every model, seed, snapshot, and test within the dbt project. This allows for full control at the task-level, improving visibility and management of data models within the team.

A bot that plays Tetris using deep reinforcement learning. The agent learns to play by training itself with a neural network and Q Learning algorithm. It explores different 'paths' to achieve higher scores and makes decisions based on predicted scores for possible moves. The game state includes attributes like lines cleared, holes, bumpiness, and total height. The agent is implemented in Python using Keras framework with a deep neural network structure. Training involves a replay queue, random sampling, and optimization techniques. Results show the agent's progress in achieving higher scores over episodes.

Cookiecutter Data Science (CCDS) is a tool for setting up a data science project template that incorporates best practices. It provides a logical, reasonably standardized but flexible project structure for doing and sharing data science work. The tool helps users to easily start new data science projects with a well-organized directory structure, including folders for data, models, notebooks, reports, and more. By following the project template created by CCDS, users can streamline their data science workflow and ensure consistency across projects.

SpeciesNet is an ensemble of AI models designed for classifying wildlife in camera trap images. It consists of an object detector that finds objects of interest in wildlife camera images and an image classifier that classifies those objects to the species level. The ensemble combines these two models using heuristics and geographic information to assign each image to a single category. The models have been trained on a large dataset of camera trap images and are used for species recognition in the Wildlife Insights platform.

Empirical is a tool that allows you to test different LLMs, prompts, and other model configurations across all the scenarios that matter for your application. With Empirical, you can run your test datasets locally against off-the-shelf models, test your own custom models and RAG applications, view, compare, and analyze outputs on a web UI, score your outputs with scoring functions, and run tests on CI/CD.

The Eureka ML Insights Framework is a repository containing code designed to help researchers and practitioners run reproducible evaluations of generative models efficiently. Users can define custom pipelines for data processing, inference, and evaluation, as well as utilize pre-defined evaluation pipelines for key benchmarks. The framework provides a structured approach to conducting experiments and analyzing model performance across various tasks and modalities.

model.nvim is a tool designed for Neovim users who want to utilize AI models for completions or chat within their text editor. It allows users to build prompts programmatically with Lua, customize prompts, experiment with multiple providers, and use both hosted and local models. The tool supports features like provider agnosticism, programmatic prompts in Lua, async and multistep prompts, streaming completions, and chat functionality in 'mchat' filetype buffer. Users can customize prompts, manage responses, and context, and utilize various providers like OpenAI ChatGPT, Google PaLM, llama.cpp, ollama, and more. The tool also supports treesitter highlights and folds for chat buffers.

The Neutone SDK is a tool designed for researchers to wrap their own audio models and run them in a DAW using the Neutone Plugin. It simplifies the process by allowing models to be built using PyTorch and minimal Python code, eliminating the need for extensive C++ knowledge. The SDK provides support for buffering inputs and outputs, sample rate conversion, and profiling tools for model performance testing. It also offers examples, notebooks, and a submission process for sharing models with the community.

llm-gemini is a plugin that provides API access to Google's Gemini models. It allows users to configure and run various Gemini models for tasks such as generating text, processing images, transcribing audio, and executing code. The plugin supports multi-modal inputs including images, audio, and video, and can output JSON objects. Additionally, it enables chat interactions with the model and supports different embedding models for text processing. Users can also run similarity searches on embedded data. The plugin is designed to work in conjunction with LLM and offers extensive documentation for development and usage.

LocalAI is a free and open-source OpenAI alternative that acts as a drop-in replacement REST API compatible with OpenAI (Elevenlabs, Anthropic, etc.) API specifications for local AI inferencing. It allows users to run LLMs, generate images, audio, and more locally or on-premises with consumer-grade hardware, supporting multiple model families and not requiring a GPU. LocalAI offers features such as text generation with GPTs, text-to-audio, audio-to-text transcription, image generation with stable diffusion, OpenAI functions, embeddings generation for vector databases, constrained grammars, downloading models directly from Huggingface, and a Vision API. It provides a detailed step-by-step introduction in its Getting Started guide and supports community integrations such as custom containers, WebUIs, model galleries, and various bots for Discord, Slack, and Telegram. LocalAI also offers resources like an LLM fine-tuning guide, instructions for local building and Kubernetes installation, projects integrating LocalAI, and a how-tos section curated by the community. It encourages users to cite the repository when utilizing it in downstream projects and acknowledges the contributions of various software from the community.

Java & Python programming assistant for AI model inference.

run the embedded code

Run mock interviews, review content and get tips to ace strategy consulting and investment banking interviews

Run Golang code in ChatGPT

I help create and run productive design thinking sessions.

Download and Run Open Source LLMs Locally.

Your new DM's screen: helping Dungeon Masters to craft & run amazing D&D adventures.

Hosts a real SQLite database and helps you create tables, make schema changes, and run SQL queries, ideal for all levels of database administration.

Meet the Restaurant Startup Guide GPT: your friendly guide in the restaurant biz. It offers casual, approachable advice to help you start and run your own restaurant with ease.

A community-building GPT based on the wildly popular Community Design™ framework from Mighty Networks. Start creating communities that run themselves.

Friendly web assistant for efficient code. Ask the wizard to create an application and you will get the HTML, CSS and Javascript code ready to run your web application.

Find trails that fit your nature for your next hike, ride, or run.

I'm your brainstorm muse in marketing and advertising; the creativity machine you need to sharpen the skills, land the job, generate the ideas, win the pitches, build the brands, ace the awards, or even run your own agency. Psst... don't let your clients find out about me! 😉

Provides running splits for Strava Routes, accounting for distance and elevation changes

Design your perfect race calendar and training plans for your next race.

Creative naming assistant for product developers

Manages office supplies to ensure smooth operations.

Giveaway bot for managing and drawing giveaway winners

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