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Make generate collab notebooks
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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": "a4ac4d55",
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"id": "32cfb8c7",
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"metadata": {},
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"source": [
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"# 🎨 Data Designer Tutorial: The Basics\n",
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{
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"cell_type": "markdown",
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"id": "988fb995",
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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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{
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"cell_type": "code",
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"### 📦 Import the essentials\n",
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{
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"cell_type": "code",
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"id": "ceff1922",
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"metadata": {},
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"from data_designer.essentials import (\n",
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" CategorySamplerParams,\n",
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" ChatCompletionInferenceParams,\n",
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" DataDesigner,\n",
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" DataDesignerConfigBuilder,\n",
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" InferenceParameters,\n",
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" LLMTextColumnConfig,\n",
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" ModelConfig,\n",
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" PersonFromFakerSamplerParams,\n",
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},
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{
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"cell_type": "markdown",
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"id": "7a4f633d",
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"metadata": {},
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"### ⚙️ Initialize the Data Designer interface\n",
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{
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"cell_type": "code",
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"cell_type": "markdown",
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"source": [
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"### 🎛️ Define model configurations\n",
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{
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" alias=MODEL_ALIAS,\n",
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" model=MODEL_ID,\n",
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" provider=MODEL_PROVIDER,\n",
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" inference_parameters=InferenceParameters(\n",
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" inference_parameters=ChatCompletionInferenceParams(\n",
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" temperature=0.5,\n",
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" top_p=1.0,\n",
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" max_tokens=1024,\n",
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},
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"cell_type": "markdown",
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"metadata": {},
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"### 🏗️ Initialize the Data Designer Config Builder\n",
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{
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"cell_type": "code",
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},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 🎲 Getting started with sampler columns\n",
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{
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"Let's start designing our product review dataset by adding product category and subcategory columns.\n"
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"cell_type": "markdown",
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"metadata": {},
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"Next, let's add samplers to generate data related to the customer and their review.\n"
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{
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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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