Skip to content

Commit a4e59e1

Browse files
committed
25.10 getting started
Signed-off-by: Johnny Greco <[email protected]>
1 parent d967961 commit a4e59e1

29 files changed

+2469
-35
lines changed

.gitignore

Lines changed: 6 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -38,3 +38,9 @@ RAG/notebooks/langchain/data/save_embedding
3838

3939
# egg-info directories
4040
**/egg-info
41+
42+
# uv exclusion
43+
uv.lock
44+
45+
# data designer exclusion
46+
data-designer-tutorial-output/

nemo/NeMo-Data-Designer/README.md

Lines changed: 12 additions & 34 deletions
Original file line numberDiff line numberDiff line change
@@ -22,48 +22,26 @@ Be sure to select this virtual environment as your kernel when running the noteb
2222

2323
## 🚀 Deploying the NeMo Data Designer Microservice
2424

25-
To run these notebooks, you'll need the NeMo Data Designer microservice. You have two deployment options:
25+
To run the tutorial notebooks in this repository, you'll need the NeMo Data Designer microservice.
26+
27+
You have two deployment options:
2628

27-
### ⚙️ Using the NeMo Data Designer Managed Service
28-
We have a [managed service of NeMo Data Designer](https://build.nvidia.com/nemo/data-designer) to help you get started quickly.
2929

30-
Please refer to the [intro-tutorials](./intro-tutorials/) notebooks to learn how to connect to this service.
30+
### 🐳 Self-Hosted Deployment
3131

32-
**Note**: This managed service of NeMo Data Designer is intended to only help you get started. As a result, it can only be used to launch `preview` jobs. It can **not** be used to launch long running jobs. If you need to launch long-running jobs please deploy an instance of [NeMo Data Designer locally](#-deploy-the-nemo-data-designer-microservice-locally)
32+
You can deploy the NeMo Data Designer microservice locally via Docker Compose.
3333

34+
Please see the [Installation Options](https://docs.nvidia.com/nemo/microservices/latest/design-synthetic-data-from-scratch-or-seeds/index.html#installation-options) section of the [NeMo Data Designer documentation](https://docs.nvidia.com/nemo/microservices/latest/design-synthetic-data-from-scratch-or-seeds/index.html) for more information.
3435

35-
### 🐳 Deploy the NeMo Data Designer Microservice Locally
3636

37-
Alternatively, you can deploy the NeMo Data Designer microservice locally via Docker Compose.
37+
### ⚙️ Using the NeMo Data Designer Managed Service
38+
We have a [managed service of NeMo Data Designer](https://build.nvidia.com/nemo/data-designer) to help you get started quickly.
3839

39-
To run the tutorial notebooks in the [advanced](./advanced/), you will need to have NeMo Data Designer deployed locally. Please see the [deployment guide](http://docs.nvidia.com/nemo/microservices/latest/set-up/deploy-as-microservices/data-designer/docker-compose.html) for more details.
40+
**Note**: This managed service of NeMo Data Designer is intended to only help you get started. As a result, it can only be used to launch `preview` jobs. It can **not** be used to launch long running jobs. If you need to launch long-running jobs please deploy an instance of NeMo Data Designer locally.
4041

4142

4243
## 📚 Tutorial Directory
4344

44-
### 🚀 Intro Tutorials
45-
46-
| Notebook | Description |
47-
|---------------------------------------------------|----------------------------------------------------------------------------------|
48-
| [1-the-basics.ipynb](./intro-tutorials/1-the-basics.ipynb) | Learn the basics of Data Designer by generating a simple product review dataset |
49-
| [2-structured-outputs-and-jinja-expressions.ipynb](./intro-tutorials/2-structured-outputs-and-jinja-expressions.ipynb) | Explore advanced data generation using structured outputs and Jinja expressions |
50-
| [3-seeding-with-a-dataset.ipynb](./intro-tutorials/3-seeding-with-a-dataset.ipynb) | Discover how to seed synthetic data generation with an external dataset |
51-
| [4-custom-model-configs.ipynb](./intro-tutorials/4-custom-model-configs.ipynb) | Master creating and using custom model configurations |
52-
53-
### 🎯 Advanced Tutorials
54-
55-
| Notebook | Domain | Description |
56-
|---------------------------------------------------|---------------------|-----------------------------------------------------------------|
57-
| [person-sampler-tutorial.ipynb](./advanced/person-samplers/person-sampler-tutorial.ipynb) | Persona Samplers | Generate realistic personas using the person sampler |
58-
| [clinical-trials.ipynb](./advanced/healthcare-datasets/clinical-trials.ipynb) | Healthcare | Build synthetic clinical trial datasets with realistic PII for testing data protection |
59-
| [insurance-claims.ipynb](./advanced/healthcare-datasets/insurance-claims.ipynb) | Healthcare | Create synthetic insurance claims datasets with realistic claim data and processing information |
60-
| [physician-notes-with-realistic-personal-details.ipynb](./advanced/healthcare-datasets/physician-notes-with-realistic-personal-details.ipynb) | Healthcare | Generate realistic patient data and physician notes with embedded personal information |
61-
| [w2-dataset.ipynb](./advanced/forms/w2-dataset.ipynb) | Forms & Documents | Generate synthetic W-2 tax form datasets with realistic employee and employer information |
62-
| [multi-turn-conversation.ipynb](./advanced/multi-turn-chat/multi-turn-conversation.ipynb) | Conversational AI | Build synthetic conversational data with realistic person details and multi-turn dialogues |
63-
| [visual-question-answering-using-vlm.ipynb](./advanced/multimodal/visual-question-answering-using-vlm.ipynb) | Multimodal | Create visual question answering datasets using Vision Language Models |
64-
| [product-question-answer-generator.ipynb](./advanced/qa-generation/product-question-answer-generator.ipynb) | Q&A Generation | Build product information datasets with corresponding questions and answers |
65-
| [generate-rag-evaluation-dataset.ipynb](./advanced/rag-examples/generate-rag-evaluation-dataset.ipynb) | RAG & Retrieval | Generate diverse RAG evaluation datasets for testing retrieval-augmented generation systems |
66-
| [reasoning-traces.ipynb](./advanced/reasoning/reasoning-traces.ipynb) | Reasoning | Build synthetic reasoning traces to demonstrate step-by-step problem-solving processes |
67-
| [text-to-python.ipynb](./advanced/text-to-code/text-to-python.ipynb) | Text-to-Code | Generate Python code from natural language instructions with validation and evaluation |
68-
| [text-to-python-evol.ipynb](./advanced/text-to-code/text-to-python-evol.ipynb) | Text-to-Code | Build advanced Python code generation with evolutionary improvements and iterative refinement |
69-
| [text-to-sql.ipynb](./advanced/text-to-code/text-to-sql.ipynb) | Text-to-Code | Create SQL queries from natural language descriptions with validation and testing |
45+
#### Self-hosted tutorials:
46+
- [Getting Started](./self-hosted-tutorials/getting-started/README.md)
47+
- [Community Contributions](./self-hosted-tutorials/community-contributions/README.md)

0 commit comments

Comments
 (0)