Best AI tools for< Isolate Stems >

Soundverse AI is an AI music generator and music assistant that allows users to create music instantly from text prompts, interact with a voice assistant for music-related help, chat with the assistant for music recommendations, extend existing tracks with new sections, isolate individual audio tracks from a mix, auto-complete songs using initial ideas, craft lyrics with AI assistance, and more. The platform offers a range of AI tools to help users iterate and personalize their music creation process, making it easy to transform ideas into music in seconds.

Melody ML is an AI-powered music processing tool that allows users to separate music tracks using machine learning technology. Users can upload songs, and the tool uses AI algorithms to extract vocals, drums, bass, and other instruments into separate stems. Melody ML offers a user-friendly platform for music enthusiasts, producers, and artists to enhance their music production process.

Music Demixer is an AI-powered application that offers advanced stem separation and automatic music transcription features. It allows users to effortlessly isolate vocals, drums, bass, melody, guitar, and piano in music tracks. The tool provides precise MIDI file generation and ensures 100% privacy by operating offline in the browser. Music Demixer is perfect for musicians, DJs, producers, and creators looking for a simple and superior solution for music editing and analysis.

Fadr is an AI music maker application that enhances creativity by providing tools for creating music using AI technology. Users can pick from a variety of tools like SynthGPT to create playable instruments with text, Remix to make remixes with Fadr AI, and Stems to extract vocals and instrument types. Fadr aims to amplify musical creativity by developing web apps and plugins that help users in making art and exploring new sounds.

StemRoller is an AI-powered application that allows users to create stems, instrumental, or acapella versions of any song. Users can simply type the name of a song into the search bar, and StemRoller will find the song online and split it into vocals, drums, bass, and other stems. Additionally, an instrumental track is created with all non-vocal stems mixed down into one track. StemRoller is free and open-source, utilizing Facebook's advanced AI and machine learning research project Demucs. Users can also donate to support the app and receive assistance on Discord for any issues or questions.

Splitter.ai is an AI-driven audio processing platform developed by a Swedish research company. It offers advanced audio processing technologies, including stem separation/extraction, reverb removal, and direct YouTube splitting. The platform is designed to assist music producers, DJs, artists, forensics engineers, audio engineers, karaoke enthusiasts, police, scientists, and more in enhancing their audio processing tasks. Splitter.ai aims to provide high-quality services through AI-driven solutions to meet the diverse needs of its users.

AudioStrip is a free online vocal isolator that allows you to remove vocals from any song. It uses artificial intelligence to separate the vocals from the music, and it does a surprisingly good job. You can use AudioStrip to create a cappella versions of your favorite songs, or you can use it to isolate the vocals from a song so that you can sing along with them. AudioStrip is easy to use. Just upload a song to the website, and then click the "Extract Vocals" button. AudioStrip will then process the song and create a new file that contains only the vocals. You can then download the new file to your computer.

Jamorphosia is an AI-powered application that allows users to remove instruments from a song. With advanced technology and audio separation capabilities, users can easily extract vocals, isolate specific instruments, and create custom backing tracks. The tool transforms audio files into personalized songs, suitable for practice or performance. Jamorphosia enhances the music experience by providing a platform for musicians to engage with original tracks in a more immersive way.

VocalRemover is an online tool that uses artificial intelligence to remove vocals from any music track. It is easy to use, simply upload your song and the AI will process it to separate the vocals from the instrumentals. You can then download the resulting karaoke version or vocals-only version of your song. VocalRemover is a great tool for musicians, singers, and anyone who wants to create their own karaoke tracks.

DisplayGateGuard is an AI-powered brand safety and suitability provider that helps advertisers choose the right placements, isolate fraudulent websites, and enhance brand safety. By leveraging artificial intelligence, the platform offers curated inclusion and exclusion lists to provide deeper insights into the environments and contexts where ads are shown, ensuring campaigns reach the right audience effectively.

Kits AI is a studio-quality AI music tool that offers a range of features for music production, including AI voice cloning, singing generators, vocal isolation, AI mastering, and more. The application empowers creators by providing tools to control their sound and explore new revenue streams. Kits AI is committed to ethical AI use, sourcing voice data responsibly, and ensuring fair compensation for artists. With a focus on advancing AI voice technology in music, Kits AI offers a variety of tools to streamline audio workflows and enhance creativity.

Audimee is an AI-powered application that offers unlimited vocals and creative freedom to users. With Audimee, users can convert vocals using royalty-free voices, train their own voices, create copyright-free cover vocals, and more. The application utilizes a reworked RVC model and superior studio recordings to provide users with high-quality and dynamic human-like voices. Audimee is designed to handle a wider range of pitches and produce fewer detectable AI artifacts, setting a new standard in vocal conversion technology.

Drumless is an AI-powered application that allows users to isolate the drums from any song and create custom backing tracks. The platform was designed to help drummers play along with their favorite band's music in a new, freer, and more creative way. Leveraging cutting-edge Artificial Intelligence technology, Drumless empowers users to unleash their creativity and musical expression. With support for MP3 and WAV formats, users can easily remove drums from songs up to 40 MB in size. Join Drumless today and experience the magic of AI music editing!

Moises is an AI-powered musician's app that allows users to remove vocals and instruments from any song. With Moises, musicians and music enthusiasts can isolate specific elements of a track for learning, remixing, or practicing purposes. The app utilizes advanced AI algorithms to provide high-quality audio separation, making it a valuable tool for music production and analysis. Moises offers a user-friendly interface and intuitive controls, making it accessible to both beginners and professionals in the music industry.

PersonaGPT is an AI-powered customer focus group tool that helps businesses understand their customers better. It provides expert-designed prompts paired with conversational AI to help businesses get instant access to insights directly from their customers' minds. PersonaGPT can be used to find out what customers think, discover what content they want, get feedback on websites and creative, highlight unique selling points, isolate pain points, and reveal partnerships with crossover brands.

crewAI is a platform for Multi AI Agents Systems that offers a user-friendly framework for automating workflows with AI agents. It simplifies the process of building and deploying multi-agent automations, providing support for various AI models and templates. With a focus on privacy and security, crewAI ensures that each agent runs in isolated environments. The platform is suitable for enterprises and developers looking to leverage AI technologies effectively.

Vivid is a tool that syncs Figma designs with your codebase by generating and updating UI code. It allows users to submit designs directly in Figma, make edits to generated divs, and sync changes with design updates. Vivid isolates design styles, making it easier for developers to focus on functionality. The tool minimizes style clutter and provides auto-updating code that tracks changes in Figma.

ChemBench is a project aimed at expanding chemistry benchmark tasks in a BIG-bench compatible way, providing a pipeline to benchmark frontier and open models. It allows users to run benchmarking tasks on models with existing presets, offering predefined parameters and processing steps. The library facilitates benchmarking models on the entire suite, addressing challenges such as prompt structure, parsing, and scoring methods. Users can contribute to the project by following the developer notes.

This repository contains the code that Defog uses for the evaluation of generated SQL. It's based off the schema from the Spider, but with a new set of hand-selected questions and queries grouped by query category. The testing procedure involves generating a SQL query, running both the 'gold' query and the generated query on their respective database to obtain dataframes with the results, comparing the dataframes using an 'exact' and a 'subset' match, logging these alongside other metrics of interest, and aggregating the results for reporting. The repository provides comprehensive instructions for installing dependencies, starting a Postgres instance, importing data into Postgres, importing data into Snowflake, using private data, implementing a query generator, and running the test with different runners.

This project provides a local, OpenAI-compatible text-to-speech (TTS) API using `edge-tts`. It emulates the OpenAI TTS endpoint (`/v1/audio/speech`), enabling users to generate speech from text with various voice options and playback speeds, just like the OpenAI API. `edge-tts` uses Microsoft Edge's online text-to-speech service, making it completely free. The project supports multiple audio formats, adjustable playback speed, and voice selection options, providing a flexible and customizable TTS solution for users.

Prometheus-Eval is a repository dedicated to evaluating large language models (LLMs) in generation tasks. It provides state-of-the-art language models like Prometheus 2 (7B & 8x7B) for assessing in pairwise ranking formats and achieving high correlation scores with benchmarks. The repository includes tools for training, evaluating, and using these models, along with scripts for fine-tuning on custom datasets. Prometheus aims to address issues like fairness, controllability, and affordability in evaluations by simulating human judgments and proprietary LM-based assessments.

Codefuse-ModelCache is a semantic cache for large language models (LLMs) that aims to optimize services by introducing a caching mechanism. It helps reduce the cost of inference deployment, improve model performance and efficiency, and provide scalable services for large models. The project facilitates sharing and exchanging technologies related to large model semantic cache through open-source collaboration.

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

Weeablind is a program that uses modern AI speech synthesis, diarization, language identification, and voice cloning to dub multi-lingual media and anime. It aims to create a pleasant alternative for folks facing accessibility hurdles such as blindness, dyslexia, learning disabilities, or simply those that don't enjoy reading subtitles. The program relies on state-of-the-art technologies such as ffmpeg, pydub, Coqui TTS, speechbrain, and pyannote.audio to analyze and synthesize speech that stays in-line with the source video file. Users have the option of dubbing every subtitle in the video, setting the start and end times, dubbing only foreign-language content, or full-blown multi-speaker dubbing with speaking rate and volume matching.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.

This repository, Awesome Efficient AIGC, collects efficient approaches for AI-generated content (AIGC) to cope with its huge demand for computing resources. It includes efficient Large Language Models (LLMs), Diffusion Models (DMs), and more. The repository is continuously improving and welcomes contributions of works like papers and repositories that are missed by the collection.

Arch is an intelligent Layer 7 gateway designed to protect, observe, and personalize AI agents with APIs. It handles tasks related to prompts, including detecting jailbreak attempts, calling backend APIs, routing between LLMs, and managing observability. Built on Envoy Proxy, it offers features like function calling, prompt guardrails, traffic management, and observability. Users can build fast, observable, and personalized AI agents using Arch to improve speed, security, and personalization of GenAI apps.

The LlamaEdge project makes it easy to run LLM inference apps and create OpenAI-compatible API services for the Llama2 series of LLMs locally. It provides a Rust+Wasm stack for fast, portable, and secure LLM inference on heterogeneous edge devices. The project includes source code for text generation, chatbot, and API server applications, supporting all LLMs based on the llama2 framework in the GGUF format. LlamaEdge is committed to continuously testing and validating new open-source models and offers a list of supported models with download links and startup commands. It is cross-platform, supporting various OSes, CPUs, and GPUs, and provides troubleshooting tips for common errors.

Microsoft Copilot for Security is a generative AI-powered assistant for daily operations in security and IT that empowers teams to protect at the speed and scale of AI.

The Vertex AI SDK for Python is a library that provides a convenient way to use the Vertex AI API. It offers a high-level interface for creating and managing Vertex AI resources, such as datasets, models, and endpoints. The SDK also provides support for training and deploying custom models, as well as using AutoML models. With the Vertex AI SDK for Python, you can quickly and easily build and deploy machine learning models on Vertex AI.

The LLM Twin Course is a free, end-to-end framework for building production-ready LLM systems. It teaches you how to design, train, and deploy a production-ready LLM twin of yourself powered by LLMs, vector DBs, and LLMOps good practices. The course is split into 11 hands-on written lessons and the open-source code you can access on GitHub. You can read everything and try out the code at your own pace.

Honcho is a platform for creating personalized AI agents and LLM powered applications for end users. The repository is a monorepo containing the server/API for managing database interactions and storing application state, along with a Python SDK. It utilizes FastAPI for user context management and Poetry for dependency management. The API can be run using Docker or manually by setting environment variables. The client SDK can be installed using pip or Poetry. The project is open source and welcomes contributions, following a fork and PR workflow. Honcho is licensed under the AGPL-3.0 License.

SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.

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

Adaptive and clear Bash guide with command execution. Learn by poking around in the code interpreter's isolated Kubernetes container!