You can launch Synthetic Data Studio on the Cloudera AI Platform to generate datasets
and evaluate them.
Agent Studio integrates with two major enterprise inference services:
- Cloudera AI Inference Service: It offers enterprise-grade deployment
options.
- AWS Bedrock: It provides scalable cloud-based inference.
Environment Variables:
All environment variables are optional if users only utilize CAII endpoints hosted in
the same cluster as the SDS application.
AWS_DEFAULT_REGION: Defaults to the us-east-1 region.AWS_ACCESS_KEY_ID: Your AWS access key ID.AWS_SECRET_ACCESS_KEY: Your AWS secret access key.Hf_token: Your Hugging Face token for exporting datasets.Hf_username: Your Hugging Face username.CDP_TOKEN: Overrides the JWT token for Cloudera AI Inference
service.
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In the Cloudera console, click
the Cloudera AI
tile.
The Cloudera AI Workbenches page displays.
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Click on the name of the workbench.
The workbenches Home page displays.
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Click Projects, and then click New
Project to create a new project.
In the left navigation pane, the new AI
Studios option is displayed.
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Click AI Studios.
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Click the Launch button in the Synthetic Data
Studio box. The Configure Studio: Synthetic Data Studio page
is displayed.
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Set the environment variables for the Synthetic Data Studio, using the details mentioned in
the prerequisites.
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Select the Runtime version.
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Click Launch AI Studio.
The Synthetic Data Studio page is displayed.
After launching, you can view the list of tasks being executed as part of the AI studio
deployment.
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After configuration, Synthetic Data Studio is displayed in the left
navigation page under AI Studios.
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Click Synthetic Data Studio and click Get
Started.
You can generate synthetic datasets for training models and evaluate the generated
datasets for fine-tuning LLMs on this page.
