From abf3823610c030f7b08a4ef5f37d7cac20ccdcf7 Mon Sep 17 00:00:00 2001
From: anastasiaguspan <happyguspan@gmail.com>
Date: Fri, 30 Jan 2026 15:00:57 -0500
Subject: [PATCH] models quickstart - new colab

Creating a new colab file to support the w&B models quickstart page: https://docs.wandb.ai/models/quickstart
For docs ticket: https://wandb.atlassian.net/browse/DOCS-1791

I have ran nb-clean on the notebook to remove metadata.
---
 colabs/intro/run_quickstart.ipynb | 123 ++++++++++++++++++++++++++++++
 1 file changed, 123 insertions(+)
 create mode 100644 colabs/intro/run_quickstart.ipynb

diff --git a/colabs/intro/run_quickstart.ipynb b/colabs/intro/run_quickstart.ipynb
new file mode 100644
index 00000000..12ded09f
--- /dev/null
+++ b/colabs/intro/run_quickstart.ipynb
@@ -0,0 +1,123 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##Use W&B to track, visualize, and manage machine learning experiments of any size.\n",
+    "To authenticate your machine with W&B, you need a W&B API key.\n",
+    "Save key to Google Colab Secrets under name WANDB_API_KEY.  Enable notebook access for key.\n",
+    "\n",
+    "A [run](/models/runs/) is a core element of W&B. You use runs to [track metrics](/models/track/), [create logs](/models/track/log/), track artifacts, and more.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install wandb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import wandb\n",
+    "import os\n",
+    "from google.colab import userdata\n",
+    "\n",
+    "os.environ[\"WANDB_API_KEY\"] = userdata.get(\"WANDB_API_KEY\")\n",
+    "\n",
+    "\n",
+    "wandb.login()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Set up project and track hyperparameters\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import wandb\n",
+    "\n",
+    "# Project that the run is recorded to\n",
+    "project = \"my-run-quickstart\"\n",
+    "\n",
+    "# Hyperparameters\n",
+    "config = {\n",
+    "    \"epochs\": 10,\n",
+    "    \"lr\": 0.01,\n",
+    "}\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "\n",
+    "## Create a machine learning training experiment\n",
+    "\n",
+    "This mock training script logs simulated accuracy and loss metrics to W&B.\n",
+    "\n",
+    "\n",
+    "Initialize a W&B run object with [`wandb.init()`](/models/ref/python/experiments/run/). Use a dictionary for the `config` parameter\n",
+    "to specify hyperparameter names and values. Within the `with` statement, you can log metrics and other information to W&B.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "import random\n",
+    "\n",
+    "\n",
+    "with wandb.init(project=project, config=config) as run:\n",
+    "    offset = random.random() / 5\n",
+    "    print(f\"lr: {config['lr']}\")\n",
+    "\n",
+    "    for epoch in range(2, config[\"epochs\"]):\n",
+    "        acc = 1 - 2**-config[\"epochs\"] - random.random() / config[\"epochs\"] - offset\n",
+    "        loss = 2**-config[\"epochs\"] + random.random() / config[\"epochs\"] + offset\n",
+    "\n",
+    "        print(f\"epoch={epoch}, accuracy={acc:.4f}, loss={loss:.4f}\")\n",
+    "        run.log({\"epoch\": epoch, \"accuracy\": acc, \"loss\": loss})\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Visit the custom \"View run\" link in the prior cell's output (or go to wandb.ai/home) to view recorded metrics such as accuracy and loss and how they changed during each training step. W&B Runs show the loss and accuracy tracked from each run. Each run object appears in the Runs page with auto-generated names."
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}