diff --git a/colabs/huggingface/Huggingface_wandb.ipynb b/colabs/huggingface/Huggingface_wandb.ipynb
index 4ff85657..a0d59a3c 100644
--- a/colabs/huggingface/Huggingface_wandb.ipynb
+++ b/colabs/huggingface/Huggingface_wandb.ipynb
@@ -1,7 +1,6 @@
 {
  "cells": [
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -10,18 +9,16 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# Hugging Face + W&B\n",
     "Visualize your [Hugging Face](https://github.com/huggingface/transformers) model's performance quickly with a seamless [W&B](https://wandb.ai/site) integration.\n",
     "\n",
-    "Compare hyperparameters, output metrics, and system stats like GPU utilization across your models. \n"
+    "Compare hyperparameters, output metrics, and system stats like GPU utilization across your models.\n"
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -31,7 +28,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -52,7 +48,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -63,7 +58,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -71,7 +65,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -104,7 +97,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -112,7 +104,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -131,7 +122,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -144,12 +134,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Optional: log both gradients and parameters\n",
-    "%env WANDB_WATCH=all"
+    "# Optional: log model checkpoints as W&B Artifacts\n",
+    "%env WANDB_LOG_MODEL=\"checkpoint\""
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -164,6 +153,7 @@
    "outputs": [],
    "source": [
     "%env WANDB_PROJECT=huggingface-demo\n",
+    "%env WANDB_LOG_MODEL=checkpoint\n",
     "%env TASK_NAME=MRPC\n",
     "\n",
     "!python run_glue.py \\\n",
@@ -177,11 +167,13 @@
     "  --num_train_epochs 3 \\\n",
     "  --output_dir /tmp/$TASK_NAME/ \\\n",
     "  --overwrite_output_dir \\\n",
-    "  --logging_steps 50"
+    "  --logging_steps 50 \\\n",
+    "  --save_steps 100 \\\n",
+    "  --eval_steps 100 \\\n",
+    "  --report_to \"wandb\""
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -199,12 +191,37 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "## Model Artifacts\n",
     "\n",
-    "### 📈 Track key information effortlessly by default\n",
+    "See an example model checkpoint and its in the UI [here](https://wandb.ai/wandb/arttest/artifacts/model/iv3_trained/5334ab69740f9dda4fed/lineage?_gl=1*yyql5q*_ga*MTQxOTYyNzExOS4xNjg0NDYyNzk1*_ga_JH1SJHJQXJ*MTY5MjMwNzI2Mi4yNjkuMS4xNjkyMzA5NjM2LjM3LjAuMA..) These artifacts store all the metadata associated with this model, the W&B runs consuming it, and the whole lineage of upstream and downstream artifacts!\n",
+    "\n",
+    "[Here's](https://wandb.ai/parambharat/huggingface-demo/runs/szfbcsd7/artifacts?workspace=) an example of the artifacts generated from the above run\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Model Registry\n",
+    "After logging a bunch of checkpoints across multiple runs during experimentation, now comes time to hand-off the best checkpoint to the next stage of the workflow (e.g. testing, deployment).\n",
+    "\n",
+    "The Model Registry is a central page that lives above individual W&B projects. It houses **Registered Models**, portfolios that store \"links\" to the valuable checkpoints living in individual W&B Projects.\n",
+    "\n",
+    "The model registry offers a centralized place to house the best checkpoints for all your model tasks. Any `model` artifact you log can be \"linked\" to a Registered Model. Pleaser refer to [this](https://docs.wandb.ai/guides/models) guide where you can find a [walkthrough](https://docs.wandb.ai/guides/models/walkthrough) of the Model Registry to learn more."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## 📈 Track key information effortlessly by default\n",
     "Weights & Biases saves a new run for each experiment. Here's the information that gets saved by default:\n",
     "- **Hyperparameters**: Settings for your model are saved in Config\n",
     "- **Model Metrics**: Time series data of metrics streaming in are saved in Log\n",
@@ -213,21 +230,19 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## 🤓 Learn more!\n",
     "- [Documentation](https://docs.wandb.com/huggingface): docs on the Weights & Biases and Hugging Face integration\n",
     "- [Videos](http://wandb.me/youtube): tutorials, interviews with practitioners, and more on our YouTube channel\n",
-    "- Contact: Message us at contact@wandb.com with questions "
+    "- Contact: Message us at contact@wandb.com with questions"
    ]
   }
  ],
  "metadata": {
   "accelerator": "GPU",
   "colab": {
-   "include_colab_link": true,
    "provenance": [],
    "toc_visible": true
   },
@@ -237,5 +252,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 4
+ "nbformat_minor": 0
 }
diff --git a/colabs/huggingface/Optimize_Hugging_Face_models_with_Weights_&_Biases.ipynb b/colabs/huggingface/Optimize_Hugging_Face_models_with_Weights_&_Biases.ipynb
index e950b3d4..58894e1e 100644
--- a/colabs/huggingface/Optimize_Hugging_Face_models_with_Weights_&_Biases.ipynb
+++ b/colabs/huggingface/Optimize_Hugging_Face_models_with_Weights_&_Biases.ipynb
@@ -143,7 +143,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%env WANDB_LOG_MODEL=true"
+    "%env WANDB_LOG_MODEL=\"checkpoint\""
    ]
   },
   {
@@ -742,7 +742,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Once you're happy with a model, don't forget to [share it with the word](https://huggingface.co/transformers/model_sharing.html) on the Model Hub!"
+    "## Model Registry\n",
+    "After logging a bunch of checkpoints across multiple runs during experimentation, now comes time to hand-off the best checkpoint to the next stage of the workflow (e.g. testing, deployment).\n",
+    "\n",
+    "The Model Registry is a central page that lives above individual W&B projects. It houses **Registered Models**, portfolios that store \"links\" to the valuable checkpoints living in individual W&B Projects.\n",
+    "\n",
+    "The model registry offers a centralized place to house the best checkpoints for all your model tasks. Any `model` artifact you log can be \"linked\" to a Registered Model. Pleaser refer to [this](https://docs.wandb.ai/guides/models) guide where you can find a [walkthrough](https://docs.wandb.ai/guides/models/walkthrough) of the Model Registry to learn more."
    ]
   },
   {
@@ -761,7 +766,7 @@
    "source": [
     "## ❓ Questions about W&B\n",
     "\n",
-    "If you have any questions about using W&B to track your model performance and predictions, please reach out to the [slack community](http://bit.ly/wandb-forum)."
+    "If you have any questions about using W&B to track your model performance and predictions, please reach out to the [discord community](https://wandb.me/discord)."
    ]
   }
  ],
diff --git a/colabs/huggingface/Visualize_your_Hugging_Face_data_with_Weights_&_Biases.ipynb b/colabs/huggingface/Visualize_your_Hugging_Face_data_with_Weights_&_Biases.ipynb
index 6be6becf..495ab6ab 100644
--- a/colabs/huggingface/Visualize_your_Hugging_Face_data_with_Weights_&_Biases.ipynb
+++ b/colabs/huggingface/Visualize_your_Hugging_Face_data_with_Weights_&_Biases.ipynb
@@ -419,8 +419,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# automatically log model to W&B at the end\n",
-    "%env WANDB_LOG_MODEL=true"
+    "# automatically log model checkpoints to W&B\n",
+    "%env WANDB_LOG_MODEL=\"checkpoint\""
    ]
   },
   {
@@ -537,6 +537,37 @@
    "source": [
     "wandb.finish()"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Model Registry\n",
+    "After logging a bunch of checkpoints across multiple runs during experimentation, now comes time to hand-off the best checkpoint to the next stage of the workflow (e.g. testing, deployment).\n",
+    "\n",
+    "The Model Registry is a central page that lives above individual W&B projects. It houses **Registered Models**, portfolios that store \"links\" to the valuable checkpoints living in individual W&B Projects.\n",
+    "\n",
+    "The model registry offers a centralized place to house the best checkpoints for all your model tasks. Any `model` artifact you log can be \"linked\" to a Registered Model. Pleaser refer to [this](https://docs.wandb.ai/guides/models) guide where you can find a [walkthrough](https://docs.wandb.ai/guides/models/walkthrough) of the Model Registry to learn more."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 📚 Resources\n",
+    "\n",
+    "* [Hugging Face and W&B integration documentation](https://docs.wandb.ai/integrations/huggingface) contains a few tips for taking most advantage of W&B\n",
+    "* [🤗 Transformers documentation](https://huggingface.co/transformers/) is extremely thorough and full of examples"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## ❓ Questions about W&B\n",
+    "\n",
+    "If you have any questions about using W&B to track your model performance and predictions, please reach out to the [discord community](https://wandb.me/discord)."
+   ]
   }
  ],
  "metadata": {