Readme

Author: jacobgil

README.md

@@ -189,7 +189,7 @@ Here you can find detailed examples of how to use this for various custom use ca
 These point to the new documentation jupter-book for fast rendering.
 The jupyter notebooks themselves can be found under the tutorials folder in the git repository.
 
-- [Notebook tutorial: XAI Recepies for the HuggingFace 🤗 Image Classification Models](<https://jacobgil.github.io/pytorch-gradcam-book/huggingface.html>)
+- [Notebook tutorial: XAI Recipes for the HuggingFace 🤗 Image Classification Models](<https://jacobgil.github.io/pytorch-gradcam-book/huggingface.html>)
 
 - [Notebook tutorial: Deep Feature Factorizations for better model explainability](<https://jacobgil.github.io/pytorch-gradcam-book/Deep%20Feature%20Factorizations.html>)
 

tutorials/HuggingFace.ipynb

@@ -1,12 +1,13 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
-   "id": "917d1776",
+   "id": "3cc7314b",
    "metadata": {},
    "source": [
-    "# XAI Recepies for the HuggingFace 🤗 Image Classification Models\n",
-    "\n",
+    "# XAI Recipes for the HuggingFace 🤗 Image Classification Models\n",
+    "![DFF](https://raw.githubusercontent.com/jacobgil/pytorch-grad-cam/master/tutorials/huggingface_dff.png)\n",
     "## Goal\n",
     "In this tutorial we will go over all (or most of?) the vision classification model families in the HuggingFace collection, and apply the pytorch gradcam package on each of them.\n",
     "\n",
@@ -222,7 +223,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "id": "ac54b490",
+   "id": "48a969be",
    "metadata": {},
    "outputs": [
     {
@@ -328,7 +329,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "id": "5207e13e",
+   "id": "80d3e305",
    "metadata": {},
    "outputs": [
     {
@@ -392,7 +393,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "id": "67c57876",
+   "id": "48545594",
    "metadata": {},
    "outputs": [
     {
@@ -464,7 +465,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "id": "540f05e8",
+   "id": "667c5d10",
    "metadata": {},
    "outputs": [
     {
@@ -538,7 +539,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "id": "3108e479",
+   "id": "95927575",
    "metadata": {},
    "outputs": [
     {
@@ -611,7 +612,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "id": "54ccaa6a",
+   "id": "e21e1fa4",
    "metadata": {},
    "outputs": [
     {
@@ -701,7 +702,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "id": "680e49de",
+   "id": "8540ccd2",
    "metadata": {},
    "outputs": [
     {
@@ -774,7 +775,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "id": "3ec0e664",
+   "id": "f18912f8",
    "metadata": {},
    "outputs": [
     {
@@ -834,7 +835,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "id": "6d9a3c93",
+   "id": "ec842eba",
    "metadata": {},
    "outputs": [
     {