TensorWave Integrations

An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.

Meta AI is an intelligent assistant that is capable of complex reasoning, following instructions, visualizing ideas, and solving nuanced problems. Meta AI is an intelligent assistant built on Meta's most advanced model. It is designed to answer any question you might have, help with writing, provide step-by-step advice, and create images to share with friends. It is available within Meta's family of apps, smart glasses, and web platforms.

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

Mosaic is an AI-powered resource planning and workforce management solution that increases profitability and productivity. It integrates with most project and financial management software to automatically gather data and show who is working on what, when. Teams can then accurately bill and forecast, effectively manage capacity, and strategically plan workloads. Mosaic rescues organizations from clunky spreadsheets and gives them the true big picture. Get started today with a free 30-day trial.

Hugging Face is a leading platform for AI and machine learning, offering a vast hub for models, datasets, and tools for natural language processing (NLP) and beyond. The platform supports a wide range of applications, from text, image, and audio to 3D data analysis. Hugging Face fosters collaboration among researchers, developers, and companies by providing open-source tools like Transformers, Diffusers, and Tokenizers. It enables users to build, share, and access pre-trained models, accelerating AI development for a variety of industries.

Ollama is an innovative platform that focuses on providing AI-powered tools and services, designed to make it easier for users to interact with and build AI-driven applications. Run AI models locally. By offering a range of solutions, including natural language processing models and customizable AI features, Ollama empowers developers, businesses, and organizations to integrate advanced machine learning technologies into their workflows. With an emphasis on usability and accessibility, Ollama strives to simplify the process of working with AI, making it an appealing option for those looking to harness the potential of artificial intelligence in their projects.

​Axolotl is an open source tool designed to streamline the fine-tuning of various AI models, offering support for multiple configurations and architectures. It enables users to train models, supporting methods like full fine-tuning, LoRA, QLoRA, ReLoRA, and GPTQ. Users can customize configurations using simple YAML files or command-line interface overrides, and load different dataset formats, including custom or pre-tokenized datasets. Axolotl integrates with technologies like xFormers, Flash Attention, Liger kernel, RoPE scaling, and multipacking, and works with single or multiple GPUs via Fully Sharded Data Parallel (FSDP) or DeepSpeed. It can be run locally or on the cloud using Docker and supports logging results and checkpoints to several platforms. It is designed to make fine-tuning AI models friendly, fast, and fun, without sacrificing functionality or scale.

​LLaMA-Factory is an open source platform designed to streamline and enhance the fine-tuning process of over 100 Large Language Models (LLMs) and Vision-Language Models (VLMs). It supports various fine-tuning techniques, including Low-Rank Adaptation (LoRA), Quantized LoRA (QLoRA), and Prefix-Tuning, allowing users to customize models efficiently. It has demonstrated significant performance improvements; for instance, its LoRA tuning offers up to 3.7 times faster training speeds with better Rouge scores on advertising text generation tasks compared to traditional methods. LLaMA-Factory's architecture is designed for flexibility, supporting a wide range of model architectures and configurations. Users can easily integrate their datasets and utilize the platform's tools to achieve optimized fine-tuning results. Detailed documentation and diverse examples are provided to assist users in navigating the fine-tuning process effectively.

AMD Radeon™ ProRender is a powerful physically-based rendering engine that enables creative professionals to produce stunningly photorealistic images. Built on AMD’s high-performance Radeon™ Rays technology, Radeon™ ProRender’s complete, scalable ray tracing engine uses open industry standards to harness GPU and CPU performance for swift, impressive results. Features an extensive native physically-based material and camera system to enable true design decisions with global illumination. A powerful combination of cross-platform compatibility, rendering capabilities, and efficiency helps reduce the time required to deliver true-to-life images. Harness the power of machine learning to produce high-quality final and interactive renders in a fraction of the time traditional denoising takes. Free Radeon™ ProRender plug-ins are currently available for many popular 3D content-creation applications to create stunning, physically accurate renders.

3U systems supporting 24, 12 or 8 nodes with 4 DIMM slots. Hot-swappable 3.5” or 2.5” NVMe/SAS3/SATA3 options. Onboard 10 Gigabit Ethernet for optimized cost-effectiveness. The MicroCloud modular architecture provides the high density, serviceability, and cost-effectiveness required for today’s demanding hyper-scale deployments. The 24/12/8 modular server nodes are conveniently integrated into a compact 3U chassis that is less than 30 inches deep, saving over 76% of rack space when compared to traditional 1U servers. The MicroCloud family offers hyper scale data center optimized single socket computing solutions with the latest lower-power and high-density system-on-chip (SoC) processors, including Intel® Xeon® E/D/E3/E5 and Intel® Atom® C Processors to enable a wide range of flexible and scalable cloud and edge computing solutions. Power and I/O ports are located at the front of the chassis for rapid server provision, upgrades, and service.