diff --git a/.github/workflows/checks.yml b/.github/workflows/checks.yml
index eea689c81..912b369e6 100644
--- a/.github/workflows/checks.yml
+++ b/.github/workflows/checks.yml
@@ -238,6 +238,7 @@ jobs:
           # - "No_Position_Experiment"
           - "Othello_GPT"
           - "Patchscopes_Generation_Demo"
+          - "Qwen"
           # - "T5"
     steps:
       - uses: actions/checkout@v3
diff --git a/demos/Qwen.ipynb b/demos/Qwen.ipynb
index fba5144ae..e2afc9b9c 100644
--- a/demos/Qwen.ipynb
+++ b/demos/Qwen.ipynb
@@ -154,7 +154,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -171,7 +171,7 @@
     "torch.set_grad_enabled(False)\n",
     "\n",
     "from transformers import AutoTokenizer\n",
-    "from transformer_lens import HookedTransformer\n",
+    "from transformer_lens.model_bridge import TransformerBridge\n",
     "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
     "from transformers.generation import GenerationConfig\n",
     "\n",
@@ -208,7 +208,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -283,12 +283,13 @@
     "    trust_remote_code = True\n",
     ").eval()\n",
     "\n",
-    "tl_model = HookedTransformer.from_pretrained_no_processing(\n",
+    "tl_model = TransformerBridge.boot_transformers(\n",
     "    model_path,\n",
     "    device=device,\n",
     "    fp32=True,\n",
     "    dtype=torch.float32,\n",
     ").to(device)\n",
+    "tl_model.enable_compatibility_mode()\n",
     "\n",
     "assert_hf_and_tl_model_are_close(hf_model, tl_model, tokenizer)"
    ]
@@ -302,7 +303,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -335,11 +336,12 @@
     "    device_map=device,\n",
     ").eval()\n",
     "\n",
-    "tl_model = HookedTransformer.from_pretrained_no_processing(\n",
+    "tl_model = TransformerBridge.boot_transformers(\n",
     "    model_path,\n",
     "    device=device,\n",
     "    dtype=torch.float32,\n",
     ").to(device)\n",
+    "tl_model.enable_compatibility_mode()\n",
     "\n",
     "assert_hf_and_tl_model_are_close(hf_model, tl_model, tokenizer)"
    ]