Business Software for VESSL AI

Google Cloud is a cloud-based service that allows you to create anything from simple websites to complex applications for businesses of all sizes. New customers get $300 in free credits to run, test, and deploy workloads. All customers can use 25+ products for free, up to monthly usage limits. Use Google's core infrastructure, data analytics & machine learning. Secure and fully featured for all enterprises. Tap into big data to find answers faster and build better products. Grow from prototype to production to planet-scale, without having to think about capacity, reliability or performance. From virtual machines with proven price/performance advantages to a fully managed app development platform. Scalable, resilient, high performance object storage and databases for your applications. State-of-the-art software-defined networking products on Google’s private fiber network. Fully managed data warehousing, batch and stream processing, data exploration, Hadoop/Spark, and messaging.

Amazon Web Services (AWS) is the world’s most comprehensive cloud platform, trusted by millions of customers across industries. From startups to global enterprises and government agencies, AWS provides on-demand solutions for compute, storage, networking, AI, analytics, and more. The platform empowers organizations to innovate faster, reduce costs, and scale globally with unmatched flexibility and reliability. With services like Amazon EC2 for compute, Amazon S3 for storage, SageMaker for AI/ML, and CloudFront for content delivery, AWS covers nearly every business and technical need. Its global infrastructure spans 120 availability zones across 38 regions, ensuring resilience, compliance, and security. Backed by the largest community of customers, partners, and developers, AWS continues to lead the cloud industry in innovation and operational expertise.

Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes builds upon 15 years of experience of running production workloads at Google, combined with best-of-breed ideas and practices from the community. Designed on the same principles that allows Google to run billions of containers a week, Kubernetes can scale without increasing your ops team. Whether testing locally or running a global enterprise, Kubernetes flexibility grows with you to deliver your applications consistently and easily no matter how complex your need is. Kubernetes is open source giving you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you effortlessly move workloads to where it matters to you.

Visual Studio Code (VS Code) is Microsoft’s open-source AI code editor designed to make coding faster, smarter, and more collaborative. It supports thousands of extensions and nearly every programming language, offering developers a lightweight yet powerful environment for writing, testing, and debugging code. With AI-powered features like GitHub Copilot, Next Edit Suggestions, and Agent Mode, VS Code helps you code with precision, automate complex tasks, and streamline development workflows. It integrates seamlessly with cloud services, remote repositories, and tools like Git, Docker, and Azure. The editor is fully customizable, allowing you to personalize your layout, color themes, and keyboard shortcuts. Whether coding locally or in the browser, VS Code delivers a complete development experience for individuals and teams alike.

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

Easily deploy cloud servers, bare metal, and storage worldwide! Our high performance compute instances are perfect for your web application or development environment. As soon as you click deploy, the Vultr cloud orchestration takes over and spins up your instance in your desired data center. Spin up a new instance with your preferred operating system or pre-installed application in just seconds. Enhance the capabilities of your cloud servers on demand. Automatic backups are extremely important for mission critical systems. Enable scheduled backups with just a few clicks from the customer portal. Our easy-to-use control panel and API let you spend more time coding and less time managing your infrastructure.

LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability.

Mixtral 8x22B is our latest open model. It sets a new standard for performance and efficiency within the AI community. It is a sparse Mixture-of-Experts (SMoE) model that uses only 39B active parameters out of 141B, offering unparalleled cost efficiency for its size. It is fluent in English, French, Italian, German, and Spanish. It has strong mathematics and coding capabilities. It is natively capable of function calling; along with the constrained output mode implemented on la Plateforme, this enables application development and tech stack modernization at scale. Its 64K tokens context window allows precise information recall from large documents. We build models that offer unmatched cost efficiency for their respective sizes, delivering the best performance-to-cost ratio within models provided by the community. Mixtral 8x22B is a natural continuation of our open model family. Its sparse activation patterns make it faster than any dense 70B model.

Meta's MusicGen is an open source, deep-learning language model that can generate short pieces of music based on text prompts. The model was trained on 20,000 hours of music, including whole tracks and individual instrument samples. The model will generate 12 seconds of audio based on the description you provided. You can optionally provide reference audio from which a broad melody will be extracted. The model will then try to follow both the description and melody provided. All samples are generated with the melody model. You can also use your own GPU or a Google Colab by following the instructions on our repo. MusicGen is comprised of a single-stage transformer LM together with efficient token interleaving patterns, which eliminates the need for cascading several models. MusicGen can generate high-quality samples, while being conditioned on textual description or melodic features, allowing better control over the generated output.

Mixtral 8x7B is a high-quality sparse mixture of experts model (SMoE) with open weights. Licensed under Apache 2.0. Mixtral outperforms Llama 2 70B on most benchmarks with 6x faster inference. It is the strongest open-weight model with a permissive license and the best model overall regarding cost/performance trade-offs. In particular, it matches or outperforms GPT-3.5 on most standard benchmarks.

We’ve integrated Llama 3 into Meta AI, our intelligent assistant, that expands the ways people can get things done, create and connect with Meta AI. You can see first-hand the performance of Llama 3 by using Meta AI for coding tasks and problem solving. Whether you're developing agents, or other AI-powered applications, Llama 3 in both 8B and 70B will offer the capabilities and flexibility you need to develop your ideas. With the release of Llama 3, we’ve updated the Responsible Use Guide (RUG) to provide the most comprehensive information on responsible development with LLMs. Our system-centric approach includes updates to our trust and safety tools with Llama Guard 2, optimized to support the newly announced taxonomy published by MLCommons expanding its coverage to a more comprehensive set of safety categories, code shield, and Cybersec Eval 2.

The open source AI model you can fine-tune, distill and deploy anywhere. Our latest instruction-tuned model is available in 8B, 70B and 405B versions. Using our open ecosystem, build faster with a selection of differentiated product offerings to support your use cases. Choose from real-time inference or batch inference services. Download model weights to further optimize cost per token. Adapt for your application, improve with synthetic data and deploy on-prem or in the cloud. Use Llama system components and extend the model using zero shot tool use and RAG to build agentic behaviors. Leverage 405B high quality data to improve specialized models for specific use cases.

FLUX.1 is a groundbreaking suite of open-source text-to-image models developed by Black Forest Labs, setting new benchmarks in AI-generated imagery with its 12 billion parameters. It surpasses established models like Midjourney V6, DALL-E 3, and Stable Diffusion 3 Ultra by offering superior image quality, detail, prompt fidelity, and versatility across various styles and scenes. FLUX.1 comes in three variants: Pro for top-tier commercial use, Dev for non-commercial research with efficiency akin to Pro, and Schnell for rapid personal and local development projects under an Apache 2.0 license. Its innovative use of flow matching and rotary positional embeddings allows for efficient and high-quality image synthesis, making FLUX.1 a significant advancement in the domain of AI-driven visual creativity.

The open-source AI model you can fine-tune, distill and deploy anywhere is now available in more versions. Choose from 1B, 3B, 11B or 90B, or continue building with Llama 3.1. Llama 3.2 is a collection of large language models (LLMs) pretrained and fine-tuned in 1B and 3B sizes that are multilingual text only, and 11B and 90B sizes that take both text and image inputs and output text. Develop highly performative and efficient applications from our latest release. Use our 1B or 3B models for on device applications such as summarizing a discussion from your phone or calling on-device tools like calendar. Use our 11B or 90B models for image use cases such as transforming an existing image into something new or getting more information from an image of your surroundings.

Over the last few weeks we all have been overwhelmed by the response and have been working hard to ensure a safe and ethical release, incorporating data from our beta model tests and community for the developers to act on. In cooperation with the tireless legal, ethics and technology teams at HuggingFace and amazing engineers at CoreWeave. We have developed an AI-based Safety Classifier included by default in the overall software package. This understands concepts and other factors in generations to remove outputs that may not be desired by the model user. The parameters of this can be readily adjusted and we welcome input from the community how to improve this. Image generation models are powerful, but still need to improve to understand how to represent what we want better.

The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Developer-friendly, fully managed, and easily scalable without infrastructure hassles. Once you have vector embeddings, manage and search through them in Pinecone to power semantic search, recommenders, and other applications that rely on relevant information retrieval. Ultra-low query latency, even with billions of items. Give users a great experience. Live index updates when you add, edit, or delete data. Your data is ready right away. Combine vector search with metadata filters for more relevant and faster results. Launch, use, and scale your vector search service with our easy API, without worrying about infrastructure or algorithms. We'll keep it running smoothly and securely.

We’ve trained and are open-sourcing a neural net called Whisper that approaches human-level robustness and accuracy in English speech recognition. Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web. We show that the use of such a large and diverse dataset leads to improved robustness to accents, background noise, and technical language. Moreover, it enables transcription in multiple languages, as well as translation from those languages into English. We are open-sourcing models and inference code to serve as a foundation for building useful applications and for further research on robust speech processing. The Whisper architecture is a simple end-to-end approach, implemented as an encoder-decoder Transformer. Input audio is split into 30-second chunks, converted into a log-Mel spectrogram, and then passed into an encoder.

Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. Developed by Google DeepMind and other teams across Google, Gemma is inspired by Gemini, and the name reflects the Latin gemma, meaning “precious stone.” Accompanying our model weights, we’re also releasing tools to support developer innovation, foster collaboration, and guide the responsible use of Gemma models. Gemma models share technical and infrastructure components with Gemini, our largest and most capable AI model widely available today. This enables Gemma 2B and 7B to achieve best-in-class performance for their sizes compared to other open models. And Gemma models are capable of running directly on a developer laptop or desktop computer. Notably, Gemma surpasses significantly larger models on key benchmarks while adhering to our rigorous standards for safe and responsible outputs.

A family of state-of-the-art, light-open models created from the same research and technology that were used to create Gemini models. These models incorporate comprehensive security measures and help ensure responsible and reliable AI solutions through selected data sets and rigorous adjustments. Gemma models achieve exceptional comparative results in their 2B, 7B, 9B, and 27B sizes, even outperforming some larger open models. With Keras 3.0, enjoy seamless compatibility with JAX, TensorFlow, and PyTorch, allowing you to effortlessly choose and change frameworks based on task. Redesigned to deliver outstanding performance and unmatched efficiency, Gemma 2 is optimized for incredibly fast inference on various hardware. The Gemma family of models offers different models that are optimized for specific use cases and adapt to your needs. Gemma models are large text-to-text lightweight language models with a decoder, trained in a huge set of text data, code, and mathematical content.