chore(sdk): Update Intro_to_Weights_&_Biases.ipynb

colabs/intro/Intro_to_Weights_&_Biases.ipynb

@@ -8,6 +8,14 @@
     "<!--- @wandbcode{intro-colab} -->"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a href=\"https://colab.research.google.com/github/wandb/examples/blob/master/colabs/intro/Intro_to_Weights_&_Biases.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>\n",
+    "<!--- @wandbcode{intro-colab} -->"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -52,10 +60,7 @@
     "# Log in to your W&B account\n",
     "import wandb\n",
     "import random\n",
-    "import math\n",
-    "\n",
-    "# Use wandb-core, temporary for wandb's new backend  \n",
-    "wandb.require(\"core\")"
+    "import math"
    ]
   },
   {
@@ -123,7 +128,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "View how your machine learning peformed in your W&B project. Copy and paste the URL link that is printed from the previous cell. The URL will redirect you to a W&B project that contains a dashboard showing graphs the show how \n",
+    "View how your machine learning peformed in your W&B project. Copy and paste the URL link that is printed from the previous cell. The URL will redirect you to a W&B project that contains a dashboard showing graphs the show how\n",
     "\n",
     "The following image shows what a dashboard can look like:"
    ]
@@ -150,10 +155,10 @@
     "[hyperparameters](https://docs.wandb.ai/ref/app/pages/run-page#overview-tab),\n",
     "[terminal output](https://docs.wandb.ai/ref/app/pages/run-page#logs-tab) and\n",
     "you'll see an [interactive table](https://docs.wandb.ai/guides/data-vis)\n",
-    "with model inputs and outputs. \n",
+    "with model inputs and outputs.\n",
     "\n",
     "### Set up PyTorch Dataloader\n",
-    "The following cell defines some useful functions that we will need to train our machine learning model. The functions themselves are not unique to W&B so we'll not cover them in detail here. See the PyTorch documentation for more information on how to define [forward and backward training loop](https://pytorch.org/tutorials/beginner/nn_tutorial.html), how to use [PyTorch DataLoaders](https://pytorch.org/tutorials/beginner/basics/data_tutorial.html) to load data in for training, and how define PyTorch models using the [`torch.nn.Sequential` Class](https://pytorch.org/docs/stable/generated/torch.nn.Sequential.html). "
+    "The following cell defines some useful functions that we will need to train our machine learning model. The functions themselves are not unique to W&B so we'll not cover them in detail here. See the PyTorch documentation for more information on how to define [forward and backward training loop](https://pytorch.org/tutorials/beginner/nn_tutorial.html), how to use [PyTorch DataLoaders](https://pytorch.org/tutorials/beginner/basics/data_tutorial.html) to load data in for training, and how define PyTorch models using the [`torch.nn.Sequential` Class](https://pytorch.org/docs/stable/generated/torch.nn.Sequential.html)."
    ]
   },
   {
@@ -223,9 +228,9 @@
     "\n",
     "The following cell is unique to W&B, so let's go over it.\n",
     "\n",
-    "In the cell we define a function called `log_image_table`. Though technically, optional, this function creates a W&B Table object. We will use the table object to create a table that shows what the model predicted for each image. \n",
+    "In the cell we define a function called `log_image_table`. Though technically, optional, this function creates a W&B Table object. We will use the table object to create a table that shows what the model predicted for each image.\n",
     "\n",
-    "More specifically, each row will conists of the image fed to the model, along with predicted value and the actual value (label). "
+    "More specifically, each row will conists of the image fed to the model, along with predicted value and the actual value (label)."
    ]
   },
   {
@@ -249,7 +254,7 @@
    "source": [
     "### Train your model and upload checkpoints\n",
     "\n",
-    "The following code trains and saves model checkpoints to your project. Use model checkpoints like you normally would to assess how the model performed during training. \n",
+    "The following code trains and saves model checkpoints to your project. Use model checkpoints like you normally would to assess how the model performed during training.\n",
     "\n",
     "W&B also makes it easy to share your saved models and model checkpoints with other members of your team or organization. To learn how to share your model and model checkpoints with members outside of your team, see [W&B Registry](https://docs.wandb.ai/guides/registry)."
    ]
@@ -345,7 +350,7 @@
    "source": [
     "## (Optional) Set up a W&B Alert\n",
     "\n",
-    "Create a [W&B Alerts](https://docs.wandb.ai/guides/track/alert) to send alerts to your Slack or email from your Python code. \n",
+    "Create a [W&B Alerts](https://docs.wandb.ai/guides/track/alert) to send alerts to your Slack or email from your Python code.\n",
     "\n",
     "There are 2 steps to follow the first time you'd like to send a Slack or email alert, triggered from your code:\n",
     "\n",
@@ -421,5 +426,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 4
+ "nbformat_minor": 0
 }