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May 14, 2026
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Release 2026-05-14 #64

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47 changes: 29 additions & 18 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -33,15 +33,15 @@ Nova Forge SDK is tested on:
* Python 3.12

### IAM Roles/Policies
* You will need an IAM role with sufficient permissions in order to use the Nova Forge SDK. You can find a list of these permissions in the `docs/iam_setup.md` file.
* You will need an IAM role with sufficient permissions in order to use the Nova Forge SDK. You can find a list of these permissions in the `docs/user-guides/iam_setup.md` file.

### Instances

Nova customization jobs also require access to enough of the right instance type to run:
- The requested instance type and count should be compatible with the requested job. The SDK will validate your instance configuration for you.
- The [SageMaker account quotas](https://docs.aws.amazon.com/general/latest/gr/sagemaker.html) for using the requested instance type in training jobs (for SMTJ) or HyperPod clusters (for SMHP) should allow the requested number of instances.
- (For SMHP) The selected HyperPod cluster should have a [Restricted Instance Group](https://docs.aws.amazon.com/sagemaker/latest/dg/nova-hp-cluster.html) with enough instances of the right type to run the requested job. The SDK will validate that your cluster contains a valid instance group.
- You can look in the `docs/instance_type_spec.md` file for the different instance types and combinations for specific jobs and methods.
- You can look in the `docs/user-guides/instance_type_spec.md` file for the different instance types and combinations for specific jobs and methods.

### HyperPod CLI

Expand Down Expand Up @@ -144,7 +144,7 @@ loader.validate(method=ValidateMethod.INVALID_RECORDS, training_method=TrainingM
loader.save("s3://my-bucket/prepared-data.jsonl")
```

For the complete guide — including column mappings, dataset splitting, filtering, chaining operations, and end-to-end examples — see **[Data Preparation Guide](docs/data_prep.md)**.
For the complete guide — including column mappings, dataset splitting, filtering, chaining operations, and end-to-end examples — see **[Data Preparation Guide](docs/user-guides/data_prep.md)**.

For a hands-on notebook walkthrough, see [`samples/dataprep_quickstart.ipynb`](samples/dataprep_quickstart.ipynb).

Expand All @@ -161,10 +161,10 @@ The Nova Forge SDK is organized into the following modules:
| **Monitor** | Job monitoring and logging | `CloudWatchLogMonitor`, `MLflowMonitor` |
| **RFT Multiturn** | Reinforcement fine-tuning infrastructure | `RFTMultiturnInfrastructure` |

* For detailed API documentation: See [`docs/spec.md`](docs/spec.md)
* For detailed API documentation: See [`docs/spec/`](docs/spec/index.md)
* For usage examples: See [`samples/nova_quickstart.ipynb`](samples/nova_quickstart.ipynb)
* For RFT Singleturn examples: See [`samples/rft_singleturn_quickstart.ipynb`](samples/rft_singleturn_quickstart.ipynb)
* For RFT Multiturn documentation: See [`docs/rft_multiturn.md`](docs/rft_multiturn.md)
* For RFT Multiturn documentation: See [`docs/user-guides/rft_multiturn.md`](docs/user-guides/rft_multiturn.md)
* For RFT Multiturn examples: See [`samples/rft_multiturn_quickstart.ipynb`](samples/rft_multiturn_quickstart.ipynb)

### Service Classes (Recommended)
Expand Down Expand Up @@ -228,16 +228,16 @@ result.show()

For the equivalent workflow using the legacy `NovaModelCustomizer`, see the [Model Module](#model-module-deprecated) section below.

For detailed API documentation on all service classes, see [`docs/spec.md`](docs/spec.md).
For detailed API documentation on all service classes, see [`docs/spec/`](docs/spec/service-classes.md).

### Dataset Module
Handles data loading, transformation, validation, filtering, and persistence for training datasets. Supports JSONL, JSON, CSV, Parquet, and Arrow formats from local files or S3.

See the [Data Preparation](#data-preparation) section above for usage overview, or the full **[Data Preparation Guide](docs/data_prep.md)** for detailed documentation.
See the [Data Preparation](#data-preparation) section above for usage overview, or the full **[Data Preparation Guide](docs/user-guides/data_prep.md)** for detailed documentation.

### Manager Module
Manages runtime infrastructure for executing training and evaluation jobs.
For the allowed instance types for each model/method combination, see `docs/instance_type_spec.md`.
For the allowed instance types for each model/method combination, see `docs/user-guides/instance_type_spec.md`.

**Main Methods:**
- `execute()` - Start a training or evaluation job
Expand Down Expand Up @@ -274,7 +274,7 @@ result = manager.scale_cluster(
target_instance_count=8
)
```
For more cluster scaling documentation, see [`docs/spec.md`](docs/spec.md).
For more cluster scaling documentation, see [`docs/spec/runtime-managers.md`](docs/spec/runtime-managers.md).

### Model Module (Deprecated)

Expand Down Expand Up @@ -400,18 +400,29 @@ Data mixing allows you to blend your custom training data with Nova's high-quali

**Key Features:**
- Available for CPT and SFT training for Nova 1 and Nova 2 (both LoRA and Full-Rank) on SageMaker HyperPod
- Available for SFT (text-only, LoRA and Full-Rank) on Nova 2 Lite on SMTJServerless
- Mix customer data (0-100%) with Nova's curated data
- Nova data categories include general knowledge and code
- Nova data percentages must sum to 100%

**Example Usage:**

```python
# Initialize with data mixing enabled
# Initialize with data mixing enabled (HyperPod)
trainer = ForgeTrainer(
model=Model.NOVA_LITE_2,
method=TrainingMethod.SFT_LORA,
infra=SMHPRuntimeManager(...), # Must use HyperPod
infra=SMHPRuntimeManager(...),
training_data_s3_path="s3://bucket/data.jsonl",
data_mixing_enabled=True,
config=ForgeConfig(output_s3_path="s3://bucket/output"),
)

# Or use SMTJServerless
trainer = ForgeTrainer(
model=Model.NOVA_LITE_2,
method=TrainingMethod.SFT_LORA,
infra=SMTJServerlessRuntimeManager(...),
training_data_s3_path="s3://bucket/data.jsonl",
data_mixing_enabled=True,
config=ForgeConfig(output_s3_path="s3://bucket/output"),
Expand All @@ -433,7 +444,7 @@ trainer.data_mixing.set_config({
```
**Important Notes:**
- The `dataset_catalog` field is system-managed and cannot be set by users
- Data mixing is only available on SageMaker HyperPod platform for Forge customers.
- Data mixing is available on SageMaker HyperPod and SMTJServerless for Forge customers.
- Refer to the [Get Forge Subscription]('https://docs.aws.amazon.com/sagemaker/latest/dg/nova-forge.html#nova-forge-prereq-access') page to enable Nova subscription in your account to use this feature.

### Job Notifications
Expand All @@ -450,7 +461,7 @@ Get email notifications when your training jobs complete, fail, or are stopped.
**Platform Support:**
- **SMTJ** (SageMaker Training Jobs): Minimal configuration required
- **SMTJServerless** (SageMaker Serverless): No instance type needed — SageMaker manages compute automatically
- **SMHP** (SageMaker HyperPod): Requires kubectl Lambda layer + additional parameters (see [`docs/spec.md`](spec.md) for more details)
- **SMHP** (SageMaker HyperPod): Requires kubectl Lambda layer + additional parameters (see [`docs/spec/runtime-managers.md`](docs/spec/runtime-managers.md) for more details)
- **Bedrock** (Amazon Bedrock): Fully managed, no infrastructure configuration required

**Quick Example:**
Expand All @@ -473,14 +484,14 @@ result.enable_job_notifications(

**Important Notes:**
- Users must confirm their email subscription by clicking the link in the AWS SNS confirmation email
- SMHP job notifications requires a kubectl Lambda layer (see [Job Notifications Guide](docs/job_notifications.md))
- SMHP job notifications requires a kubectl Lambda layer (see [Job Notifications Guide](docs/user-guides/job_notifications.md))
- Notification infrastructure is created once per region (SMTJ) or once per cluster (SMHP) and shared across jobs.
- See [`docs/job_notifications.md`](docs/job_notifications.md) for detailed setup instructions, troubleshooting, and advanced usage
- See [`docs/spec.md`](docs/spec.md) for complete API documentation on job notifications.
- See [`docs/user-guides/job_notifications.md`](docs/user-guides/job_notifications.md) for detailed setup instructions, troubleshooting, and advanced usage
- See [`docs/spec/notifications.md`](docs/spec/notifications.md) for complete API documentation on job notifications.

### Batch Sample Tracing

Diagnose gradient spikes by identifying which training data lines were used in a specific training step. Enable with `enable_batch_sample_tracing=True` on `ForgeTrainer`, then call `trainer.trace_batch(result, step=N)` after the job completes. See [`docs/spec.md`](docs/spec.md) for full API details.
Diagnose gradient spikes by identifying which training data lines were used in a specific training step. Enable with `enable_batch_sample_tracing=True` on `ForgeTrainer`, then call `trainer.trace_batch(result, step=N)` after the job completes. See [`docs/spec/service-classes.md`](docs/spec/service-classes.md) for full API details.

---
## Telemetry
Expand All @@ -497,7 +508,7 @@ This comprehensive SDK enables end-to-end customization of Amazon Nova models wi

To get started customizing Nova models, please see the following files:
* Notebook with "quick start" examples to start customizing at `samples/nova_quickstart.ipynb`
* Specification document with detailed information about each module at `docs/spec.md`
* Specification document with detailed information about each module at [`docs/spec/`](docs/spec/index.md)

---
## Security Best Practices for SDK Users
Expand Down
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