# Nova Forge access and setup for
To set up Amazon Nova Forge for use with Jobs, you need to:
+ Subscribe to Amazon Nova Forge
+ Set up a cluster
**Topics**
+ [Subscribe to Amazon Nova Forge](nova-forge-subscribing.md)
+ [Set up infrastructure](nova-forge-hyperpod-setup.md)
+ [Responsible AI](nova-forge-responsible-ai.md)
# Subscribe to Amazon Nova Forge
To access Amazon Nova Forge features, complete the following steps:
1. Verify administrator access to the AWS account.
1. Navigate to the SageMaker AI console and request access to Amazon Nova Forge.
1. Wait for the Amazon Nova team to email a confirmation after the subscription request is approved.
1. Tag your execution role with the `forge-subscription` tag. This tag is required for accessing Amazon Nova Forge features and checkpoints. Add the following tag to your execution role:
+ Key: `forge-subscription`
+ Value: `true`
**Note**
Standard Amazon Nova features remain available without a Forge subscription. Amazon Nova Forge is designed for building custom frontier models with control and flexibility across all model training phases.
# Set up infrastructure
Once your Amazon Nova Forge subscription is approved, set up the necessary infrastructure to use Forge-enabled features. For detailed instructions on creating a EKS cluster with a restricted instance group (RIG), follow the [workshop instructions](https://catalog.us-east-1.prod.workshops.aws/workshops/dcac6f7a-3c61-4978-8344-7535526bf743/en-US).
# Responsible AI
**Content moderation settings**: Amazon Nova Forge customers have access to Customizable Content Moderation Settings (CCMS) for Amazon Nova Lite 1.0 and Pro 1.0 models. CCMS allows you to adjust content moderation controls to align with your specific business requirements while maintaining essential responsible AI safeguards. To determine if your business use case qualifies for CCMS, contact your Amazon Web Services account manager.
Amazon Nova Forge provides a Responsible AI Toolkit that includes training data, evaluation benchmarks, and runtime controls to help you align your models with Amazon Nova's responsible AI guidelines.
**Training data**: The "RAI" category in data mixing contains cases and scenarios emphasizing responsible AI principles, safety considerations, and responsible technology deployment. Use these to align your models responsibly during continued pre-training.
**Evaluations**: Benchmark tasks are available to test your model's ability to detect and reject inappropriate, harmful, or incorrect content. Use these evaluations to measure the difference between base model performance and your custom model performance.
**Runtime controls**: By default, Amazon Nova's runtime controls moderate model responses during inference. To modify these controls for your specific business case, request Customizable Content Moderation Settings (CCMS) by contacting your Amazon Web Services account manager.
## Shared Responsibility for Safety
Safety is a shared responsibility between Amazon Web Services and our customers. Changing the base model or using continued pre-training to improve performance on a specific use case can impact safety, fairness, and other properties of the new model.
We use a robust adaptation method to minimize changes to the safety, fairness, and other protections built into our base models while minimizing impact on model performance for tasks the model was not customized for.
You are responsible for:
+ End-to-end testing of their applications on datasets representative of their use cases
+ Deciding if test results meet their specific expectations of safety, fairness, and other properties, as well as overall effectiveness
For more information, see the Amazon Web Services Responsible Use of AI Guide, Amazon Web Services Responsible AI Policy, AWS Acceptable Use Policy, and AWS Service Terms for the services you plan to use.
## Customizable Content Moderation Settings (CCMS)
CCMS allows you to adjust controls relevant to your business requirements while maintaining essential, non-configurable controls that ensure responsible use of AI.
These settings allow content generation through three available configurations:
+ Security only
+ Safety, sensitive content, and fairness combined
+ All categories combined
The four content moderation categories are:
1. **Safety** – Covers dangerous activities, weapons, and controlled substances
1. **Sensitive content** – Includes profanity, nudity, and bullying
1. **Fairness** – Addresses bias and cultural considerations
1. **Security** – Involves cybercrime, malware, and malicious content
Regardless of your CCMS configuration, Amazon Amazon Nova enforces essential, non-configurable controls to ensure responsible use of AI, such as controls to prevent harm to children and preserve privacy.
### Recommendations for Using CCMS
When using CCMS, we recommend using Continuous Pre Training (CPT) and starting from a pre-RAI alignment checkpoint (PRE-TRAINING-Early, PRE-TRAINING-Mid, or PRE-TRAINING-Final) rather than the GA/FINAL checkpoint. These checkpoints have not undergone safety training or been steered toward specific RAI behaviors, allowing you to customize them more efficiently to your content moderation requirements.
**Tip**: When using CCMS with data mixing, consider adjusting the "rai" category percentage in your nova\$1data configuration to align with your specific content moderation requirements.
### Availability
CCMS is currently available for approved customers using:
+ Nova Lite 1.0 and Pro 1.0 models
+ Amazon Bedrock On-Demand inference
+ The us-east-1 (N. Virginia) region
To enable CCMS for your Forge models, contact your Amazon Web Services account manager.