updating links

Signed-off-by: Kieran Fraser <Kieran.Fraser@ibm.com>

app.py

@@ -53,6 +53,14 @@ div.svelte-15lo0d8>*, div.svelte-15lo0d8>.form > * {
 }
 """
 
+global model 
+model = transformers.AutoModelForImageClassification.from_pretrained(
+        'facebook/deit-tiny-distilled-patch16-224',
+        ignore_mismatched_sizes=True,
+        force_download=True,
+        num_labels=10
+    )
+
 def sample_imagenette():
     import torchvision
     label_names = [
@@ -113,12 +121,7 @@ def clf_poison_evaluate(*args):
 
     target_class = label_names.index(target_class)
     
-    model = transformers.AutoModelForImageClassification.from_pretrained(
-        'facebook/deit-tiny-distilled-patch16-224',
-        ignore_mismatched_sizes=True,
-        force_download=True,
-        num_labels=10
-    )
+    
     optimizer = torch.optim.Adam(model.parameters(), lr=1e-4)
     loss_fn = torch.nn.CrossEntropyLoss()
 
@@ -142,7 +145,7 @@ def clf_poison_evaluate(*args):
     train_dataset = torchvision.datasets.ImageFolder(root="./data/imagenette2-320/train", transform=transform)
     labels = np.asarray(train_dataset.targets)
     classes = np.unique(labels)
-    samples_per_class = 10
+    samples_per_class = 20
 
     x_subset = []
     y_subset = []
@@ -226,6 +229,10 @@ def show_params(type):
         return gr.Column(visible=True)
     return gr.Column(visible=False)  
 
+head_script = '''
+<script async defer src="https://buttons.github.io/buttons.js"></script>
+'''
+
 # e.g. To use a local alternative theme: carbon_theme = Carbon()
 carbon_theme = Carbon()
 with gr.Blocks(css=css, theme='Tshackelton/IBMPlex-DenseReadable') as demo:
@@ -248,12 +255,15 @@ with gr.Blocks(css=css, theme='Tshackelton/IBMPlex-DenseReadable') as demo:
                 common red-team workflow to assess model vulnerability to data poisoning attacks 🧪</p>''')
     
     gr.Markdown('''<p style="font-size: 18px; text-align: justify"><i>Check out the full suite of features provided by ART <a href="https://github.com/Trusted-AI/adversarial-robustness-toolbox"
-                    target="blank_">here</a>.</i>
-                    add link to notebook</p>''')
-    
+                    target="blank_">here</a>. To dive further into poisoning attacks with Hugging Face and ART, check out our 
+                    <a href="https://github.com/Trusted-AI/adversarial-robustness-toolbox/blob/main/notebooks/hugging_face_poisoning.ipynb" 
+                    target="_blank">notebook</a>. Also feel free to contribute and give our repo a ⭐.</i></p>''')
+
     gr.Markdown('''<hr/>''')
     
     
+    
+    
     with gr.Row(elem_classes=["larger-gap", "custom-text"]):
         with gr.Column(scale=1):
             gr.Markdown('''<p style="font-size: 20px; text-align: justify">ℹ️ First lets set the scene. You have a dataset of images, such as Imagenette.</p>''')
@@ -287,28 +297,28 @@ with gr.Blocks(css=css, theme='Tshackelton/IBMPlex-DenseReadable') as demo:
         with gr.Column(scale=1):
             attack = gr.Textbox(visible=True, value="Backdoor", label="Attack", interactive=False)
             target_class = gr.Radio(label="Target class", info="The class you wish to force the model to predict.",
-                                        choices=['dog',
+                                        choices=['church',
                                         'cassette player',
                                         'chainsaw',
-                                        'church',
+                                        'dog',
                                         'french horn',
                                         'garbage truck',
                                         'gas pump',
                                         'golf ball',
-                                        'parachutte',], value='dog')
+                                        'parachutte',], value='church')
             eval_btn_patch = gr.Button("Evaluate")
     with gr.Row(elem_classes="custom-text"):
         with gr.Column(scale=10):
-            clean_gallery = gr.Gallery(label="Clean", preview=False, show_download_button=True)
+            clean_gallery = gr.Gallery(label="Clean", preview=False, show_download_button=True, height=600)
             clean_accuracy = gr.Number(label="Clean Accuracy", precision=2)
         with gr.Column(scale=1, min_width='0px', elem_classes='symbols'):
             gr.Markdown('''➕''')
-        with gr.Column(scale=5):
+        with gr.Column(scale=5, elem_classes='symbols'):
             trigger_image = gr.Image(label="Trigger Image",  value="./baby-on-board.png", interactive=False)
         with gr.Column(scale=1, min_width='0px'):
             gr.Markdown('''🟰''', elem_classes='symbols')
         with gr.Column(scale=10):
-            poison_gallery = gr.Gallery(label="Poisoned", preview=False, show_download_button=True)
+            poison_gallery = gr.Gallery(label="Poisoned", preview=False, show_download_button=True, height=600)
             poison_success = gr.Number(label="Poison Success", precision=2)
         
     eval_btn_patch.click(clf_poison_evaluate, inputs=[attack, trigger_image, target_class],

poisoned_models/deit_imagenette_poisoned_model_2.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:39f8f6f68436a69a2c06b480934eda88e2279e3b03db5226ed6b55eef16cce61
+size 22201811