Best AI tools for< Back-test Models >

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.

DipSway is an AI-powered crypto trading platform that offers zero-configuration, full autopilot trading bots. The platform uses proprietary AI models trained to recognize market opportunities by analyzing technical indicators and pattern detectors. DipSway allows users to connect to their exchange, turn on autopilot, and start trading without the need for manual intervention. With features like live backtests, historical performance data, and extendable configurations via TradingView, DipSway aims to simplify and optimize crypto trading for users of all experience levels.

STRATxAI is an AI-driven investment strategy platform that offers customized alpha-generating portfolios for modern investors. The platform, developed by a team of quantitative hedge fund professionals and machine-learning engineers, leverages advanced AI and proprietary quantitative technology to streamline the creation, implementation, and management of bespoke, data-driven investment strategies. With a focus on innovation and adaptability, STRATxAI model portfolios harness extensive data to deliver client-centric customization and risk-adjusted returns. The Alana Investor Platform provides an intuitive design catering to both no-code and know-code professional users, offering portfolio optimization, data-driven insights, and smart rebalancing for optimal asset allocation and effective risk management.

Inductor is a developer tool for evaluating, ensuring, and improving the quality of your LLM applications – both during development and in production. It provides a fantastic workflow for continuous testing and evaluation as you develop, so that you always know your LLM app’s quality. Systematically improve quality and cost-effectiveness by actionably understanding your LLM app’s behavior and quickly testing different app variants. Rigorously assess your LLM app’s behavior before you deploy, in order to ensure quality and cost-effectiveness when you’re live. Easily monitor your live traffic: detect and resolve issues, analyze usage in order to improve, and seamlessly feed back into your development process. Inductor makes it easy for engineering and other roles to collaborate: get critical human feedback from non-engineering stakeholders (e.g., PM, UX, or subject matter experts) to ensure that your LLM app is user-ready.

Composer is an AI-powered platform designed for investing, offering users the ability to build trading algorithms with AI, backtest them, and execute trades all in one place. The platform does not require coding skills and provides a user-friendly experience for creating and managing investment strategies. Composer aims to make sophisticated quant investing accessible to all users, regardless of their level of expertise.

Trade Ideas is an AI-driven stock scanning and charting platform designed to meet the needs of active traders. It provides powerful tools such as real-time market scanning, AI-driven trade signals, customizable alerts, advanced charting capabilities, and time-saving data visualization. Trade Ideas offers users the confidence to make smarter trading decisions and the freedom to conquer markets anytime, anywhere. The platform also includes features like a trading simulator for practicing new strategies, Picture in Picture charts for visualizing multiple timeframes, and integration with leading brokers and trading platforms.

Trade Ideas is an AI-driven stock scanning and charting platform that provides unmatched precision in finding the biggest movers first. It offers AI-powered Buy/Sell signals, real-time market scanning, customizable alerts, advanced charting capabilities, and time-saving data visualization. Users can access the platform on any device, empowering them to make smarter trading decisions and stay ahead of the game. Trade Ideas also features a live trading room with expert market commentary and a simulator for practicing new trading strategies under actual market conditions. The platform is trusted by leading brokers and trading platforms, offering users a competitive edge in the market.

The Trading AI is a generative AI financial platform that revolutionizes investment decisions. It offers an all-in-one solution for portfolio management, AI-assisted strategies, backtesting, and algorithmic trading. The platform features an intuitive user-friendly interface, lightning-fast backtesting, advanced live dashboard, and a strategy builder requiring no programming skills. Users can join the VIP Club for exclusive advantages, participate in tournaments, and monetize their strategies in the marketplace. The platform leverages AI to provide data-backed intelligence for optimized trading decisions.

StockHero is a highly-rated stock trading bot that allows users to trade intelligently with a high win rate. The platform offers preset bots from the Marketplace for users to deploy in minutes, automating trades on leading brokerages. StockHero caters to users of all levels, from beginners to experienced traders, providing features like TradingView integration, Strategy Designer, and advanced indicator settings. The platform also offers a White-Glove Service for personalized guidance, paper trading for risk-free practice, and an AI ChatBot for financial queries. With a focus on risk management and user satisfaction, StockHero aims to enhance the trading experience for all users.

Koxy AI is an AI-powered serverless back-end platform that allows users to build globally distributed, fast, secure, and scalable back-ends with no code required. It offers features such as live logs, smart errors handling, integration with over 80,000 AI models, and more. Koxy AI is designed to help users focus on building the best service possible without wasting time on security and latency concerns. It provides a No-SQL JSON-based database, real-time data synchronization, cloud functions, and a drag-and-drop builder for API flows.

Rosebud is an AI-powered journaling app that makes it easy for anyone to build and maintain an impactful journaling practice. With personalized questions and real-time feedback, Rosebud makes journaling easy and rewarding. Rosebud also resurfaces key details and insights when you need them most, and analyzes your thoughts, organizing them into themes and topics for you to explore.

PhotoRestore.io is a free AI photo restoration service that specializes in restoring old or damaged photos. Using state-of-the-art algorithms, the platform can repair blurry, faded, and damaged photos to provide clear, high-quality images. PhotoRestore.io aims to bring faded memories back to life and help users preserve their precious moments. The service prioritizes user privacy and data security, offering a seamless experience for restoring photos and creating lasting keepsakes for generations to come.

Up Learn is an AI-powered educational platform designed to help students improve their A Level grades with a guarantee of achieving A*/A results or a money-back offer. The platform offers interactive videos covering the entire curriculum, detailed progress tracking, personalized revision based on AI algorithms, exam-board specific courses, guided exam practice, and 24/7 tutor support. Up Learn aims to make learning simple and efficient, ensuring that every second of study counts towards exam success.

Rosetta AI is an e-commerce marketing platform that uses artificial intelligence to help businesses acquire qualified traffic, personalize interactions, and strengthen member repurchases. It offers a range of solutions, including personalized recommendations, AI-powered advertising, interactive experiences, product label generation, and automated marketing. Rosetta AI is used by over 2000 enterprise and SMB websites worldwide and has helped clients increase their click-through rate, average order value, check-out conversion, and revenue.

Image Colorizer is an AI-powered photo editing tool that allows users to colorize, restore, enhance, retouch, and repair old photos. It uses advanced AI technology to automatically and instantly restore old photos, bringing them back to life. The tool is easy to use and offers a wide range of features to help users improve and restore their old pictures.

Gling AI is a desktop application that uses artificial intelligence and machine learning to automatically edit videos by removing unwanted silences and disfluencies. It supports videos in multiple languages and can be integrated with popular video editing software such as Final Cut Pro, DaVinci Resolve, and Adobe Premiere. Gling AI is designed to save video creators time and effort in the editing process.

Respaid is a B2B collections tool that focuses on respectful and efficient debt recovery. It utilizes AI-powered precision messaging to optimize communication with debtors, resulting in a 50% collection rate and 30x faster performance than traditional methods. The tool offers features such as direct payments, database cleaning, and insights into why customers aren't paying. Respaid aims to protect your brand reputation while helping you recover unpaid invoices in a respectful manner.

Relationship 2.0 is an AI-powered system designed to help individuals navigate through breakups, personal development, and rebuilding healthy relationships. By leveraging advanced AI technology, the platform offers personalized guidance, tailored plans, and expert advice to assist users in overcoming emotional challenges, understanding relationship dynamics, and fostering positive growth. Relationship 2.0 aims to provide a comprehensive solution for individuals seeking to improve themselves and reconnect with their ex-partners in a healthy and sustainable manner.

Nero Platinum Suite is a comprehensive software collection for Windows PCs that provides a wide range of multimedia capabilities, including burning, managing, optimizing, and editing photos, videos, and music files. It includes various AI-powered features such as the Nero AI Image Upscaler, Nero AI Video Upscaler, and Nero AI Photo Tagger, which enhance and simplify multimedia tasks.

Circleboom is an AI-powered social media management tool that enables users, brands, and SMBs to grow and strengthen their social accounts. It offers a wide range of features such as RSS feed integration, post scheduling, AI post generation, hashtag generation, and account analytics. Circleboom focuses on simplicity and intuitive design to provide users with easy-to-use tools for managing their social media presence effectively. Trusted by professionals, Circleboom aims to help users expand their social circle and achieve their social media goals.

Qlib is an open-source, AI-oriented quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It covers the entire chain of quantitative investment, from alpha seeking to order execution. The platform empowers researchers to explore ideas and implement productions using AI technologies in quantitative investment. Qlib collaboratively solves key challenges in quantitative investment by releasing state-of-the-art research works in various paradigms. It provides a full ML pipeline for data processing, model training, and back-testing, enabling users to perform tasks such as forecasting market patterns, adapting to market dynamics, and modeling continuous investment decisions.

T-MAC is a kernel library that directly supports mixed-precision matrix multiplication without the need for dequantization by utilizing lookup tables. It aims to boost low-bit LLM inference on CPUs by offering support for various low-bit models. T-MAC achieves significant speedup compared to SOTA CPU low-bit framework (llama.cpp) and can even perform well on lower-end devices like Raspberry Pi 5. The tool demonstrates superior performance over existing low-bit GEMM kernels on CPU, reduces power consumption, and provides energy savings. It achieves comparable performance to CUDA GPU on certain tasks while delivering considerable power and energy savings. T-MAC's method involves using lookup tables to support mpGEMM and employs key techniques like precomputing partial sums, shift and accumulate operations, and utilizing tbl/pshuf instructions for fast table lookup.

The AirBnB Clone - The Console project is the first segment of the AirBnB project at Holberton School, aiming to cover fundamental concepts of higher level programming. The goal is to deploy a server as a simple copy of the AirBnB Website (HBnB). The project includes a command interpreter to manage objects for the AirBnB website, allowing users to create new objects, retrieve objects, perform operations on objects, update object attributes, and destroy objects. The project is interpreted/tested on Ubuntu 14.04 LTS using Python 3.4.3.

GPTel is a simple Large Language Model chat client for Emacs, with support for multiple models and backends. It's async and fast, streams responses, and interacts with LLMs from anywhere in Emacs. LLM responses are in Markdown or Org markup. Supports conversations and multiple independent sessions. Chats can be saved as regular Markdown/Org/Text files and resumed later. You can go back and edit your previous prompts or LLM responses when continuing a conversation. These will be fed back to the model. Don't like gptel's workflow? Use it to create your own for any supported model/backend with a simple API.

This repository showcases how to deploy generative AI models from Amazon SageMaker JumpStart using the AWS CDK. Generative AI is a type of AI that can create new content and ideas, such as conversations, stories, images, videos, and music. The repository provides a detailed guide on deploying image and text generative AI models, utilizing pre-trained models from SageMaker JumpStart. The web application is built on Streamlit and hosted on Amazon ECS with Fargate. It interacts with the SageMaker model endpoints through Lambda functions and Amazon API Gateway. The repository also includes instructions on setting up the AWS CDK application, deploying the stacks, using the models, and viewing the deployed resources on the AWS Management Console.

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

A curated list of Generative AI projects, tools, artworks, and models

The 'ai-dev-2024-ml-workshop' repository contains materials for the Deploy and Monitor ML Pipelines workshop at the AI_dev 2024 conference in Paris, focusing on deployment designs of machine learning pipelines using open-source applications and free-tier tools. It demonstrates automating data refresh and forecasting using GitHub Actions and Docker, monitoring with MLflow and YData Profiling, and setting up a monitoring dashboard with Quarto doc on GitHub Pages.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

ChainForge is a visual programming environment for battle-testing prompts to LLMs. It is geared towards early-stage, quick-and-dirty exploration of prompts, chat responses, and response quality that goes beyond ad-hoc chatting with individual LLMs. With ChainForge, you can: * Query multiple LLMs at once to test prompt ideas and variations quickly and effectively. * Compare response quality across prompt permutations, across models, and across model settings to choose the best prompt and model for your use case. * Setup evaluation metrics (scoring function) and immediately visualize results across prompts, prompt parameters, models, and model settings. * Hold multiple conversations at once across template parameters and chat models. Template not just prompts, but follow-up chat messages, and inspect and evaluate outputs at each turn of a chat conversation. ChainForge comes with a number of example evaluation flows to give you a sense of what's possible, including 188 example flows generated from benchmarks in OpenAI evals. This is an open beta of Chainforge. We support model providers OpenAI, HuggingFace, Anthropic, Google PaLM2, Azure OpenAI endpoints, and Dalai-hosted models Alpaca and Llama. You can change the exact model and individual model settings. Visualization nodes support numeric and boolean evaluation metrics. ChainForge is built on ReactFlow and Flask.

This package integrates Large Language Models (LLMs) into spaCy, featuring a modular system for **fast prototyping** and **prompting** , and turning unstructured responses into **robust outputs** for various NLP tasks, **no training data** required. It supports open-source LLMs hosted on Hugging Face 🤗: Falcon, Dolly, Llama 2, OpenLLaMA, StableLM, Mistral. Integration with LangChain 🦜️🔗 - all `langchain` models and features can be used in `spacy-llm`. Tasks available out of the box: Named Entity Recognition, Text classification, Lemmatization, Relationship extraction, Sentiment analysis, Span categorization, Summarization, Entity linking, Translation, Raw prompt execution for maximum flexibility. Soon: Semantic role labeling. Easy implementation of **your own functions** via spaCy's registry for custom prompting, parsing and model integrations. For an example, see here. Map-reduce approach for splitting prompts too long for LLM's context window and fusing the results back together

Can AI Code is a self-evaluating interview tool for AI coding models. It includes interview questions written by humans and tests taken by AI, inference scripts for common API providers and CUDA-enabled quantization runtimes, a Docker-based sandbox environment for validating untrusted Python and NodeJS code, and the ability to evaluate the impact of prompting techniques and sampling parameters on large language model (LLM) coding performance. Users can also assess LLM coding performance degradation due to quantization. The tool provides test suites for evaluating LLM coding performance, a webapp for exploring results, and comparison scripts for evaluations. It supports multiple interviewers for API and CUDA runtimes, with detailed instructions on running the tool in different environments. The repository structure includes folders for interviews, prompts, parameters, evaluation scripts, comparison scripts, and more.

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust 🦀, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python 🐍, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic

This repository contains self-trained single image super resolution (SISR) models. The models are trained on various datasets and use different network architectures. They can be used to upscale images by 2x, 4x, or 8x, and can handle various types of degradation, such as JPEG compression, noise, and blur. The models are provided as safetensors files, which can be loaded into a variety of deep learning frameworks, such as PyTorch and TensorFlow. The repository also includes a number of resources, such as examples, results, and a website where you can compare the outputs of different models.

MisguidedAttention is a collection of prompts designed to challenge the reasoning abilities of large language models by presenting them with modified versions of well-known thought experiments, riddles, and paradoxes. The goal is to assess the logical deduction capabilities of these models and observe any shortcomings or fallacies in their responses. The repository includes a variety of prompts that test different aspects of reasoning, such as decision-making, probability assessment, and problem-solving. By analyzing how language models handle these challenges, researchers can gain insights into their reasoning processes and potential biases.

QANTA is a system and dataset for question answering tasks. It provides a script to download datasets, preprocesses questions, and matches them with Wikipedia pages. The system includes various datasets, training, dev, and test data in JSON and SQLite formats. Dependencies include Python 3.6, `click`, and NLTK models. Elastic Search 5.6 is needed for the Guesser component. Configuration is managed through environment variables and YAML files. QANTA supports multiple guesser implementations that can be enabled/disabled. Running QANTA involves using `cli.py` and Luigi pipelines. The system accesses raw Wikipedia dumps for data processing. The QANTA ID numbering scheme categorizes datasets based on events and competitions.

Aider is an AI pair programming tool that allows users to collaborate with large language models (LLMs) to edit code in their local git repository. It works best with GPT-4o & Claude 3.5 Sonnet and can connect to almost any LLM. Users can run Aider with specific files, request changes, add new features or test cases, describe bugs, refactor code, update docs, and more. Aider automatically commits changes with sensible messages, supports multiple programming languages, and can handle complex requests by editing multiple files at once. It uses a map of the entire git repo for efficient performance in larger codebases. Users can chat with Aider, add images, URLs, and even code with their voice. Aider has achieved top scores on SWE Bench, solving real GitHub issues from popular open source projects like django, scikitlearn, matplotlib, etc.

Assistant multilingue pour Jest

Helps build full stack apps with React.

stunspot's simulation of an expert Node.js dev. Defaults to Bengali bilingual.

Developer for Chrome Extensions Manifest V3

Expert in JavaScript coding and execution

Pine Script 5+ Digital Professor

Pinescript version 5 coding expert for TradingView.

A specialized GPT for developing cryptocurrency trading strategies on Moralis Money

Zorro-Trader.com

Your Pine Script V5 guide.

MT4/MT5 EA development advisor

Provides accurate TraderJS functionalities based on user docs.

TradingView代码专家，所有回答都用中文。

Friendly, educated assistant for Pine Script v5.

Drives efficient back-end processes through innovative coding and software solutions.

I'm Back Propagation, here to help you understand and apply back propagation techniques to your AI models.

World Knowledge Expert with Step Back Prompting.

I'm Wendy, your go-to for witty Wendy's slogans and sassy clap backs!

Concise, witty Clippers debate champ.

Clever assistant for sharp 'clap backs', keeps details private. Join our Reddit community: https://www.reddit.com/r/GPTreview/