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Shutterstock ImageAI

Meet Shutterstock ImageAI, a new text‑to-image diffusion model codeveloped by Shutterstock and Databricks

ImageAI is our new text-to-image diffusion model built using the advanced capabilities of Databricks Mosaic AI and trained exclusively on Shutterstock’s proprietary image repository. ImageAI generates photorealistic images based on trusted data.

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A wide technology dbrx card


DBRX is an open source, commercially usable LLM developed by our team at Databricks and released in March 2024. As of its release, it is the highest-quality open source model available. Thanks to its sparse mixture-of-expert architecture, it is also fast, fitting these extraordinary capabilities into just 36B active parameters.

Shutterstock ImageAI, powered by Databricks

Shutterstock ImageAI, powered by Databricks

ImageAI is trained exclusively on Shutterstock’s repository to create high-resolution images based on trusted data.

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Mosaic BERT

Pretrain your own BERT model on your data from scratch using Mosaic AI for $20.

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The MPT models are a family of open source, commercially usable LLMs released in summer 2023. They include MPT-30B (prioritizing quality) and MPT-7B (prioritizing efficiency). You can download versions of these models that we have trained or you can train your own MPT models on your data using the Mosaic AI Multi-Cloud Training (MCT) product.

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Mosaic Diffusion

Mosaic Diffusion is a generative model that turns text descriptions into images, designed to be highly efficient.

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Composer is an open source deep-learning training library optimized for scalability and usability.

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LLM Foundry

Databricks LLM Foundry is a highly efficient, open source codebase for training, fine-tuning and evaluating LLMs.

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Our deep learning stack is the most efficient for training, fine-tuning and deploying large models at scale.

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StreamingDataset is an open source PyTorch DataLoader that makes it easy and efficient to stream training datasets.

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Evaluation Gauntlet

The Evaluation Gauntlet is a library for evaluating the quality of generative language models.

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