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docs: fix links on notebooks and add %%capture on install cell (#134)
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‎docs/colab_notebooks/1-the-basics.ipynb‎

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"cells": [
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{
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"cell_type": "markdown",
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"id": "39d7d274",
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"metadata": {},
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"source": [
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"# 🎨 Data Designer Tutorial: The Basics\n",
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"cell_type": "markdown",
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"id": "60f1d002",
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"metadata": {},
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"source": [
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"### ⚡ Colab Setup\n",
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{
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"cell_type": "code",
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"id": "99c42292",
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install -qU data-designer"
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"%%capture\n",
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"!pip install -U data-designer"
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{
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"cell_type": "code",
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"cell_type": "markdown",
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"id": "bc185897",
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"metadata": {},
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"### 📦 Import the essentials\n",
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"### ⚙️ Initialize the Data Designer interface\n",
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"\n",
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"- `DataDesigner` is the main object is responsible for managing the data generation process.\n",
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"\n",
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"- When initialized without arguments, the [default model providers](https://nvidia-nemo.github.io/DataDesigner/concepts/models/default-model-settings/) are used.\n"
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"- When initialized without arguments, the [default model providers](https://nvidia-nemo.github.io/DataDesigner/latest/concepts/models/default-model-settings/) are used.\n"
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"### 🎛️ Define model configurations\n",
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"\n",
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"- The \"model alias\" is used to reference the model in the Data Designer config (as we will see below).\n",
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"- 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",
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"- 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",
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"- By default, we use [build.nvidia.com](https://build.nvidia.com/models) as the model provider.\n"
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"### 🏗️ Initialize the Data Designer Config Builder\n",
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"## 🎲 Getting started with sampler columns\n",
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"Let's start designing our product review dataset by adding product category and subcategory columns.\n"
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"Next, let's add samplers to generate data related to the customer and their review.\n"
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"## 🦜 LLM-generated columns\n",
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"### 🔁 Iteration is key – preview the dataset!\n",
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"### 📊 Analyze the generated data\n",
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"### 🆙 Scale up!\n",
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"## ⏭️ Next Steps\n",
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"Now that you've seen the basics of Data Designer, check out the following notebooks to learn more about:\n",
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"- [Structured outputs and jinja expressions](/notebooks/2-structured-outputs-and-jinja-expressions/)\n",
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"- [Structured outputs and jinja expressions](https://nvidia-nemo.github.io/DataDesigner/latest/notebooks/2-structured-outputs-and-jinja-expressions/)\n",
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"- [Seeding synthetic data generation with an external dataset](/notebooks/3-seeding-with-a-dataset/)\n"
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"- [Seeding synthetic data generation with an external dataset](https://nvidia-nemo.github.io/DataDesigner/latest/notebooks/3-seeding-with-a-dataset/)\n",
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"\n",
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"- [Providing images as context](https://nvidia-nemo.github.io/DataDesigner/latest/notebooks/4-providing-images-as-context/)\n"
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