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andreatgretel merged 1 commit into from
Dec 15, 2025
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docs: fix links on notebooks and add %%capture on install cell #134

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75 changes: 39 additions & 36 deletions docs/colab_notebooks/1-the-basics.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "markdown",
"id": "a4ac4d55",
"id": "39d7d274",
"metadata": {},
"source": [
"# 🎨 Data Designer Tutorial: The Basics\n",
Expand All @@ -14,7 +14,7 @@
},
{
"cell_type": "markdown",
"id": "9e9f3c47",
"id": "60f1d002",
"metadata": {},
"source": [
"### ⚡ Colab Setup\n",
Expand All @@ -25,17 +25,18 @@
{
"cell_type": "code",
"execution_count": null,
"id": "41b31194",
"id": "99c42292",
"metadata": {},
"outputs": [],
"source": [
"!pip install -qU data-designer"
"%%capture\n",
"!pip install -U data-designer"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "502b3aba",
"id": "2c959ca9",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -52,7 +53,7 @@
},
{
"cell_type": "markdown",
"id": "8c512fbc",
"id": "bc185897",
"metadata": {},
"source": [
"### 📦 Import the essentials\n",
Expand All @@ -63,7 +64,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "8fae521f",
"id": "dc3a2d9d",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -84,20 +85,20 @@
},
{
"cell_type": "markdown",
"id": "e71d0256",
"id": "36c5f571",
"metadata": {},
"source": [
"### ⚙️ Initialize the Data Designer interface\n",
"\n",
"- `DataDesigner` is the main object is responsible for managing the data generation process.\n",
"\n",
"- When initialized without arguments, the [default model providers](https://nvidia-nemo.github.io/DataDesigner/concepts/models/default-model-settings/) are used.\n"
"- When initialized without arguments, the [default model providers](https://nvidia-nemo.github.io/DataDesigner/latest/concepts/models/default-model-settings/) are used.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "68fc7172",
"id": "61b23c70",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -106,7 +107,7 @@
},
{
"cell_type": "markdown",
"id": "9a821a27",
"id": "3c9b7cb6",
"metadata": {},
"source": [
"### 🎛️ Define model configurations\n",
Expand All @@ -115,15 +116,15 @@
"\n",
"- The \"model alias\" is used to reference the model in the Data Designer config (as we will see below).\n",
"\n",
"- The \"model provider\" is the external service that hosts the model (see the [model config](https://nvidia-nemo.github.io/DataDesigner/concepts/models/default-model-settings/) docs for more details).\n",
"- The \"model provider\" is the external service that hosts the model (see the [model config](https://nvidia-nemo.github.io/DataDesigner/latest/concepts/models/default-model-settings/) docs for more details).\n",
"\n",
"- By default, we use [build.nvidia.com](https://build.nvidia.com/models) as the model provider.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a9515141",
"id": "b86f6217",
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -155,7 +156,7 @@
},
{
"cell_type": "markdown",
"id": "3b940ab9",
"id": "1f089871",
"metadata": {},
"source": [
"### 🏗️ Initialize the Data Designer Config Builder\n",
Expand All @@ -170,7 +171,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "ec21da7e",
"id": "3d666193",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -179,7 +180,7 @@
},
{
"cell_type": "markdown",
"id": "85b2324e",
"id": "e88c8881",
"metadata": {},
"source": [
"## 🎲 Getting started with sampler columns\n",
Expand All @@ -196,7 +197,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "f49f435e",
"id": "79fb85c6",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -205,7 +206,7 @@
},
{
"cell_type": "markdown",
"id": "f582b642",
"id": "5106cc10",
"metadata": {},
"source": [
"Let's start designing our product review dataset by adding product category and subcategory columns.\n"
Expand All @@ -214,7 +215,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "8cfc43b1",
"id": "22b97af1",
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -295,7 +296,7 @@
},
{
"cell_type": "markdown",
"id": "2d0eea21",
"id": "4857b085",
"metadata": {},
"source": [
"Next, let's add samplers to generate data related to the customer and their review.\n"
Expand All @@ -304,7 +305,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "b5e65724",
"id": "9e90b3cb",
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -341,7 +342,7 @@
},
{
"cell_type": "markdown",
"id": "e6788771",
"id": "b36a153b",
"metadata": {},
"source": [
"## 🦜 LLM-generated columns\n",
Expand All @@ -356,7 +357,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "a2705cd9",
"id": "4da88fe6",
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -393,7 +394,7 @@
},
{
"cell_type": "markdown",
"id": "e3dd2f69",
"id": "5f1b9ac8",
"metadata": {},
"source": [
"### 🔁 Iteration is key – preview the dataset!\n",
Expand All @@ -410,7 +411,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "c6e43147",
"id": "543e2f9c",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -420,7 +421,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "fab77d01",
"id": "26136a8a",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -431,7 +432,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "875ee6a6",
"id": "aca4360d",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -441,7 +442,7 @@
},
{
"cell_type": "markdown",
"id": "87b59e4b",
"id": "35ca0470",
"metadata": {},
"source": [
"### 📊 Analyze the generated data\n",
Expand All @@ -454,7 +455,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "5d347f4c",
"id": "d55b402d",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -464,7 +465,7 @@
},
{
"cell_type": "markdown",
"id": "d2fb84f2",
"id": "245b48cf",
"metadata": {},
"source": [
"### 🆙 Scale up!\n",
Expand All @@ -477,7 +478,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "71a31e85",
"id": "fc803eb0",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -487,7 +488,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "501e9092",
"id": "881c2043",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -500,7 +501,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "6f217b4a",
"id": "d79860d4",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -512,16 +513,18 @@
},
{
"cell_type": "markdown",
"id": "4da82b0f",
"id": "b4b45176",
"metadata": {},
"source": [
"## ⏭️ Next Steps\n",
"\n",
"Now that you've seen the basics of Data Designer, check out the following notebooks to learn more about:\n",
"\n",
"- [Structured outputs and jinja expressions](/notebooks/2-structured-outputs-and-jinja-expressions/)\n",
"- [Structured outputs and jinja expressions](https://nvidia-nemo.github.io/DataDesigner/latest/notebooks/2-structured-outputs-and-jinja-expressions/)\n",
"\n",
"- [Seeding synthetic data generation with an external dataset](/notebooks/3-seeding-with-a-dataset/)\n"
"- [Seeding synthetic data generation with an external dataset](https://nvidia-nemo.github.io/DataDesigner/latest/notebooks/3-seeding-with-a-dataset/)\n",
"\n",
"- [Providing images as context](https://nvidia-nemo.github.io/DataDesigner/latest/notebooks/4-providing-images-as-context/)\n"
]
}
],
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