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Fine-tuning and evaluating LLMs with SuperAnnotate & Snowflake

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Large language models (LLMs) are becoming a crucial foundation for businesses seeking to extract more value from their data.  Snowflake makes it easy to start with LLMs using Snowflake Cortex AI, allowing users to select from well-known models from companies like Mistral, Meta, and others.  However, implementing LLMs comes with challenges, particularly ensuring that the models meet quality and cost requirements.

In the journey to getting these models to production, enterprises are finding value in fine-tuning LLMs on use-case-specific data to achieve optimal performance.  A fine-tuned model can be more accurate and cheaper to serve given its smaller size. A key step to fine tuning is the effort of taking raw, semistructured data and transforming it into a viable dataset for fine tuning.

SuperAnnotate + Snowflake = accelerated LLM adoption

SuperAnnotate and Snowflake have partnered to help businesses overcome the complexities of deploying LLMs, ensuring they can leverage the full potential of their data efficiently and securely.

superannotate snowflake

This no code integration allows customers to establish an active learning pipeline between Snowflake and SuperAnnotate.  Customers can curate their Snowflake data in SuperAnnotate’s platform for a variety of fine-tuning workflows, such as dataset creation and model evaluation. Customers can build repeatable workflows using a flexible UI and then choose whether to use their own staff or SuperAnnotate’s services for manual data curation.

Once the dataset for fine tuning is created, customers can set up an orchestration pipeline to push the updated data to their Snowflake environment for downstream use as training data in Snowflake Cortex AI Fine Tuning. Customers can continue using SuperAnnotate to evaluate and refine this model over time.

"Data is the centerpiece of AI, and Cortex AI is key in bringing that data to life. Our collaboration with Snowflake enables our customers to create custom AI applications faster with a quality of output they can trust.” Vahan Petrosyan, Co-Founder CEO, SuperAnnotate.
"With the integration of SuperAnnotate’s robust data curation platform and Cortex AI, our customers can seamlessly transform raw data into finely-tuned datasets, ensuring their models are accurate, efficient, and ready for production. " Sean Chen PM Snowflake Cortex AI.

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