feat: NVIDIA beginner e2e notebook

llama_stack/providers/remote/datasetio/nvidia/README.md

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+# NVIDIA DatasetIO Provider for LlamaStack
+
+This provider enables dataset management using NVIDIA's NeMo Customizer service.
+
+## Features
+
+- Register datasets for fine-tuning LLMs
+- Unregister datasets
+
+## Getting Started
+
+### Prerequisites
+
+- LlamaStack with NVIDIA configuration
+- Access to Hosted NVIDIA NeMo Microservice
+- API key for authentication with the NVIDIA service
+
+### Setup
+
+Build the NVIDIA environment:
+
+```bash
+llama stack build --template nvidia --image-type conda
+```
+
+### Basic Usage using the LlamaStack Python Client
+
+#### Initialize the client
+
+```python
+import os
+
+os.environ["NVIDIA_API_KEY"] = "your-api-key"
+os.environ["NVIDIA_CUSTOMIZER_URL"] = "http://nemo.test"
+os.environ["NVIDIA_USER_ID"] = "llama-stack-user"
+os.environ["NVIDIA_DATASET_NAMESPACE"] = "default"
+os.environ["NVIDIA_PROJECT_ID"] = "test-project"
+from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
+
+client = LlamaStackAsLibraryClient("nvidia")
+client.initialize()
+```
+
+#### Register a dataset
+
+```python
+client.datasets.register(
+    purpose="post-training/messages",
+    dataset_id="my-training-dataset",
+    source={"type": "uri", "uri": "hf://datasets/default/sample-dataset"},
+    metadata={
+        "format": "json",
+        "description": "Dataset for LLM fine-tuning",
+        "provider": "nvidia",
+    },
+)
+```
+
+#### Get a list of all registered datasets
+
+```python
+datasets = client.datasets.list()
+for dataset in datasets:
+    print(f"Dataset ID: {dataset.identifier}")
+    print(f"Description: {dataset.metadata.get('description', '')}")
+    print(f"Source: {dataset.source.uri}")
+    print("---")
+```
+
+#### Unregister a dataset
+
+```python
+client.datasets.unregister(dataset_id="my-training-dataset")
+```