diff --git a/maze_transformer/test_helpers/assertions.py b/maze_transformer/test_helpers/assertions.py
index 49e5164a..93c76079 100644
--- a/maze_transformer/test_helpers/assertions.py
+++ b/maze_transformer/test_helpers/assertions.py
@@ -93,7 +93,8 @@ def assert_model_output_equality(
         )
         if not torch.all(output_argsort_match):
             raise ModelOutputArgsortEqualityError(
-                f"argsort not equal, {output_argsort_match.numel() - output_argsort_match.sum()} / {output_argsort_match.numel()} elements differ"
+                f"argsort not equal, {output_argsort_match.numel() - output_argsort_match.sum()} / {output_argsort_match.numel()} elements differ",
+                f"{vocab_size = }, {test_sequence_length = }",
             )
 
     # apply normalization (e.g. softmax) and check with atol v-small
diff --git a/poetry.lock b/poetry.lock
index ba4758cd..2897ba4b 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -31,92 +31,119 @@ test-prod = ["parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "py
 test-trackers = ["comet-ml", "dvclive", "tensorboard", "wandb"]
 testing = ["bitsandbytes", "datasets", "diffusers", "evaluate", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
 
+[[package]]
+name = "aiohappyeyeballs"
+version = "2.4.0"
+description = "Happy Eyeballs for asyncio"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"},
+]
+
 [[package]]
 name = "aiohttp"
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 optional = false
 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
+aiohappyeyeballs = ">=2.3.0"
 aiosignal = ">=1.1.2"
 async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""}
 attrs = ">=17.3.0"
@@ -125,7 +152,7 @@ multidict = ">=4.5,<7.0"
 yarl = ">=1.0,<2.0"
 
 [package.extras]
-speedups = ["Brotli", "aiodns", "brotlicffi"]
+speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"]
 
 [[package]]
 name = "aiosignal"
@@ -295,32 +322,32 @@ files = [
 
 [[package]]
 name = "attrs"
-version = "23.2.0"
+version = "24.2.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"},
+    {file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"},
 ]
 
 [package.extras]
-cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[tests]", "pre-commit"]
-docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
-tests = ["attrs[tests-no-zope]", "zope-interface"]
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 [package.dependencies]
@@ -737,63 +779,83 @@ test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"]
 
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@@ -804,17 +866,18 @@ toml = ["tomli"]
 
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 description = "Generate coverage badges for Coverage.py."
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 [package.dependencies]
 coverage = "*"
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 [[package]]
 name = "cycler"
@@ -833,75 +896,77 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
 [[package]]
 name = "datasets"
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 [[package]]
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 [package.extras]
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 [[package]]
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 [package.dependencies]
@@ -3792,223 +3890,233 @@ jupyter = ["ipywidgets (>=7.5.1,<9)"]
 
 [[package]]
 name = "rpds-py"
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@@ -4212,13 +4320,13 @@ files = [
 
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@@ -4245,10 +4353,11 @@ httpx = ["httpx (>=0.16.0)"]
 huey = ["huey (>=2)"]
 huggingface-hub = ["huggingface-hub (>=0.22)"]
 langchain = ["langchain (>=0.0.210)"]
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 loguru = ["loguru (>=0.5)"]
 openai = ["openai (>=1.0.0)", "tiktoken (>=0.3.0)"]
 opentelemetry = ["opentelemetry-distro (>=0.35b0)"]
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 pure-eval = ["asttokens", "executing", "pure-eval"]
 pymongo = ["pymongo (>=3.1)"]
 pyspark = ["pyspark (>=2.4.4)"]
@@ -4362,19 +4471,19 @@ test = ["pytest"]
 
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+test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test", "mypy (==1.11.*)", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy", "pytest-perf", "pytest-ruff (<0.4)", "pytest-ruff (>=0.2.1)", "pytest-ruff (>=0.3.2)", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
 
 [[package]]
 name = "shellingham"
@@ -4422,13 +4531,13 @@ files = [
 
 [[package]]
 name = "soupsieve"
-version = "2.5"
+version = "2.6"
 description = "A modern CSS selector implementation for Beautiful Soup."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "soupsieve-2.5-py3-none-any.whl", hash = "sha256:eaa337ff55a1579b6549dc679565eac1e3d000563bcb1c8ab0d0fefbc0c2cdc7"},
-    {file = "soupsieve-2.5.tar.gz", hash = "sha256:5663d5a7b3bfaeee0bc4372e7fc48f9cff4940b3eec54a6451cc5299f1097690"},
+    {file = "soupsieve-2.6-py3-none-any.whl", hash = "sha256:e72c4ff06e4fb6e4b5a9f0f55fe6e81514581fca1515028625d0f299c602ccc9"},
+    {file = "soupsieve-2.6.tar.gz", hash = "sha256:e2e68417777af359ec65daac1057404a3c8a5455bb8abc36f1a9866ab1a51abb"},
 ]
 
 [[package]]
@@ -4452,13 +4561,13 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
 [[package]]
 name = "sympy"
-version = "1.13.1"
+version = "1.13.2"
 description = "Computer algebra system (CAS) in Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "sympy-1.13.1-py3-none-any.whl", hash = "sha256:db36cdc64bf61b9b24578b6f7bab1ecdd2452cf008f34faa33776680c26d66f8"},
-    {file = "sympy-1.13.1.tar.gz", hash = "sha256:9cebf7e04ff162015ce31c9c6c9144daa34a93bd082f54fd8f12deca4f47515f"},
+    {file = "sympy-1.13.2-py3-none-any.whl", hash = "sha256:c51d75517712f1aed280d4ce58506a4a88d635d6b5dd48b39102a7ae1f3fcfe9"},
+    {file = "sympy-1.13.2.tar.gz", hash = "sha256:401449d84d07be9d0c7a46a64bd54fe097667d5e7181bfe67ec777be9e01cb13"},
 ]
 
 [package.dependencies]
@@ -4469,13 +4578,13 @@ dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"]
 
 [[package]]
 name = "tenacity"
-version = "8.5.0"
+version = "9.0.0"
 description = "Retry code until it succeeds"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "tenacity-8.5.0-py3-none-any.whl", hash = "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687"},
-    {file = "tenacity-8.5.0.tar.gz", hash = "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78"},
+    {file = "tenacity-9.0.0-py3-none-any.whl", hash = "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539"},
+    {file = "tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b"},
 ]
 
 [package.extras]
@@ -4676,13 +4785,13 @@ files = [
 
 [[package]]
 name = "tomlkit"
-version = "0.13.0"
+version = "0.13.2"
 description = "Style preserving TOML library"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "tomlkit-0.13.0-py3-none-any.whl", hash = "sha256:7075d3042d03b80f603482d69bf0c8f345c2b30e41699fd8883227f89972b264"},
-    {file = "tomlkit-0.13.0.tar.gz", hash = "sha256:08ad192699734149f5b97b45f1f18dad7eb1b6d16bc72ad0c2335772650d7b72"},
+    {file = "tomlkit-0.13.2-py3-none-any.whl", hash = "sha256:7a974427f6e119197f670fbbbeae7bef749a6c14e793db934baefc1b5f03efde"},
+    {file = "tomlkit-0.13.2.tar.gz", hash = "sha256:fff5fe59a87295b278abd31bec92c15d9bc4a06885ab12bcea52c71119392e79"},
 ]
 
 [[package]]
@@ -4760,13 +4869,13 @@ files = [
 
 [[package]]
 name = "tqdm"
-version = "4.66.4"
+version = "4.66.5"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.66.4-py3-none-any.whl", hash = "sha256:b75ca56b413b030bc3f00af51fd2c1a1a5eac6a0c1cca83cbb37a5c52abce644"},
-    {file = "tqdm-4.66.4.tar.gz", hash = "sha256:e4d936c9de8727928f3be6079590e97d9abfe8d39a590be678eb5919ffc186bb"},
+    {file = "tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd"},
+    {file = "tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad"},
 ]
 
 [package.dependencies]
@@ -4795,13 +4904,13 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 
 [[package]]
 name = "transformer-lens"
-version = "2.2.2"
+version = "2.4.0"
 description = "An implementation of transformers tailored for mechanistic interpretability."
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
-    {file = "transformer_lens-2.2.2-py3-none-any.whl", hash = "sha256:81b091d23b914481dd40a6db05d5adff29202000159bcf1a0db0d68e07e6b1a9"},
-    {file = "transformer_lens-2.2.2.tar.gz", hash = "sha256:08682b80c051807ac10fb7590942a18ec7f9392c8b58c7debeaee3bec5975fbc"},
+    {file = "transformer_lens-2.4.0-py3-none-any.whl", hash = "sha256:f3b6286367454f98440e87ab2ef87c6c26710ff051a4c8fc9d01e733e1493963"},
+    {file = "transformer_lens-2.4.0.tar.gz", hash = "sha256:b6a5dd87bcec43e7d12a4ca52b1bfdc13366d627a796aec9f9dfda93be4e442e"},
 ]
 
 [package.dependencies]
@@ -4830,13 +4939,13 @@ wandb = ">=0.13.5"
 
 [[package]]
 name = "transformers"
-version = "4.43.3"
+version = "4.44.1"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "transformers-4.43.3-py3-none-any.whl", hash = "sha256:6552beada5d826c25ff9b79139d237ab9050c6ea96b73d7fd2f8a8ba23ee76a4"},
-    {file = "transformers-4.43.3.tar.gz", hash = "sha256:820c5b192bb1bf47250802901a8f0bf581e06b8fded89179d4ef08a1e903ee1c"},
+    {file = "transformers-4.44.1-py3-none-any.whl", hash = "sha256:bd2642da18b4e6d29b135c17650cd7ca8e874f2d092d2eddd3ed6b71a93a155c"},
+    {file = "transformers-4.44.1.tar.gz", hash = "sha256:3b9a1a07ca65c665c7bf6109b7da76182184d10bb58d9ab14e6892e7b9e073a2"},
 ]
 
 [package.dependencies]
@@ -4859,10 +4968,10 @@ audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 benchmark = ["optimum-benchmark (>=0.2.0)"]
 codecarbon = ["codecarbon (==1.2.0)"]
 deepspeed = ["accelerate (>=0.21.0)", "deepspeed (>=0.9.3)"]
-deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.21.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
-dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
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-dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
+deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.21.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
+dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
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+dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
 flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
 flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 ftfy = ["ftfy"]
@@ -4873,17 +4982,17 @@ natten = ["natten (>=0.14.6,<0.15.0)"]
 onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
 onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
 optuna = ["optuna"]
-quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "ruff (==0.4.4)", "urllib3 (<2.0.0)"]
+quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "ruff (==0.5.1)", "urllib3 (<2.0.0)"]
 ray = ["ray[tune] (>=2.7.0)"]
 retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
-ruff = ["ruff (==0.4.4)"]
+ruff = ["ruff (==0.5.1)"]
 sagemaker = ["sagemaker (>=2.31.0)"]
 sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
 serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
 sigopt = ["sigopt"]
 sklearn = ["scikit-learn"]
 speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
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 [[package]]
@@ -5365,13 +5490,13 @@ pandas = ["pandas (>=1.5.3)"]
 
 [[package]]
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+    {file = "zipp-3.20.0.tar.gz", hash = "sha256:0145e43d89664cfe1a2e533adc75adafed82fe2da404b4bbb6b026c0157bdb31"},
 ]
 
 [package.extras]
@@ -5381,4 +5506,4 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools",
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.13"
-content-hash = "2f39a218130a10deefead7ff01f8083e876fabb201e9edca27354b41a20dabcb"
+content-hash = "adb68dc5faad8c231fb4dcc8b1e628479cd9dd34b0217b89c7a5d1d7857fc4cf"
diff --git a/pyproject.toml b/pyproject.toml
index 3c04b6e2..5c793c1d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -13,7 +13,7 @@ python = ">=3.10,<3.13"
 maze-dataset = "^0.5.6"
 # transformers
 torch = "^2.4.0"
-transformer-lens = "^2.2.2"
+transformer-lens = "^2.4.0"
 # transformers = ">=4.34" # Dependency in transformer-lens 1.14.0
 # utils
 muutils = "^0.6.7"
diff --git a/tests/unit/maze_transformer/training/zanj/test_zanj_ht_save_load.py b/tests/unit/maze_transformer/training/zanj/test_zanj_ht_save_load.py
index 8faf4dd6..ae8085f7 100644
--- a/tests/unit/maze_transformer/training/zanj/test_zanj_ht_save_load.py
+++ b/tests/unit/maze_transformer/training/zanj/test_zanj_ht_save_load.py
@@ -1,6 +1,8 @@
 from pathlib import Path
 
+import pytest
 from maze_dataset import MazeDatasetConfig
+from maze_dataset.tokenization import MazeTokenizer, TokenizationMode
 from zanj import ZANJ
 from zanj.torchutil import assert_model_exact_equality
 
@@ -12,58 +14,106 @@
     ZanjHookedTransformer,
 )
 
-ZANJ_MODEL_CFG: ConfigHolder = ConfigHolder(
-    train_cfg=TrainConfig(name="test_cfg_save-train"),
-    dataset_cfg=MazeDatasetConfig(name="test_cfg_save-data", grid_n=5, n_mazes=10),
-    model_cfg=BaseGPTConfig(
-        name="test_cfg_save-model",
-        act_fn="relu",  # need an actual function here since HookedTransformer will complain otherwise
-        d_model=128,
-        d_head=64,
-        n_layers=4,
-    ),
-)
-
-MODEL: ZanjHookedTransformer = ZanjHookedTransformer(ZANJ_MODEL_CFG)
-MODEL_FROM_CFG_CREATE: ZanjHookedTransformer = ZANJ_MODEL_CFG.create_model_zanj()
-
-
-def test_configs_setup_correct():
-    assert MODEL.zanj_model_config == ZANJ_MODEL_CFG
-    assert MODEL.cfg == ZANJ_MODEL_CFG.hooked_transformer_cfg
-
-    assert MODEL_FROM_CFG_CREATE.zanj_model_config == ZANJ_MODEL_CFG
-    assert MODEL_FROM_CFG_CREATE.cfg == ZANJ_MODEL_CFG.hooked_transformer_cfg
-
-
-def test_model_save_exact():
-    fname: Path = Path("tests/_temp/test_model_save_nofold.zanj")
+ZANJ_MODEL_CFGS: list[ConfigHolder] = [
+    ConfigHolder(
+        name=f"test-{mt_name}",
+        train_cfg=TrainConfig(name="test_cfg_save-train"),
+        dataset_cfg=MazeDatasetConfig(name="test_cfg_save-data", grid_n=5, n_mazes=10),
+        model_cfg=BaseGPTConfig(
+            name="test_cfg_save-model",
+            act_fn="relu",  # need an actual function here since HookedTransformer will complain otherwise
+            d_model=64,
+            d_head=16,
+            n_layers=4,
+        ),
+        maze_tokenizer=mt,
+    )
+    for mt_name, mt in [
+        ("None", None),
+        (
+            "raster",
+            MazeTokenizer(
+                tokenization_mode=TokenizationMode.AOTP_UT_rasterized, max_grid_size=10
+            ),
+        ),
+        (
+            "uniform",
+            MazeTokenizer(
+                tokenization_mode=TokenizationMode.AOTP_UT_uniform, max_grid_size=10
+            ),
+        ),
+        (
+            "indexed",
+            MazeTokenizer(
+                tokenization_mode=TokenizationMode.AOTP_CTT_indexed, max_grid_size=10
+            ),
+        ),
+    ]
+]
+
+
+MODELS: list[tuple[ConfigHolder, ZanjHookedTransformer]] = [
+    (cfg, ZanjHookedTransformer(cfg)) for cfg in ZANJ_MODEL_CFGS
+]
+
+
+@pytest.mark.parametrize("cfg_model", MODELS, ids=lambda x: x[0].name)
+def test_configs_setup_correct(cfg_model: tuple[ConfigHolder, ZanjHookedTransformer]):
+    cfg: ConfigHolder
+    model: ZanjHookedTransformer
+    cfg, model = cfg_model
+    assert model.zanj_model_config == cfg
+    assert model.cfg == cfg.hooked_transformer_cfg
+
+
+@pytest.mark.parametrize("cfg_model", MODELS, ids=lambda x: x[0].name)
+def test_model_save_exact(cfg_model: tuple[ConfigHolder, ZanjHookedTransformer]):
+    cfg: ConfigHolder
+    model: ZanjHookedTransformer
+    cfg, model = cfg_model
+    name: str = cfg.name
+
+    fname: Path = Path(f"tests/_temp/test_model_save_nofold-{name}.zanj")
     fname.parent.mkdir(parents=True, exist_ok=True)
     zanj: ZANJ = ZANJ(
         custom_settings={"_load_state_dict_wrapper": {"recover_exact": True}},
     )
-    print(f"{MODEL.zanj_model_config.dataset_cfg = }")
-    zanj.save(MODEL, fname)
+    print(f"{model.zanj_model_config.dataset_cfg = }")
+    zanj.save(model, fname)
     model_load = zanj.read(fname)
 
-    assert_model_exact_equality(MODEL, model_load)
-    assert_model_output_equality(MODEL, model_load)
+    assert_model_exact_equality(model, model_load)
+    assert_model_output_equality(model, model_load)
 
 
-def test_model_save_fold_ln():
-    fname: Path = Path("tests/_temp/test_model_save.zanj")
+@pytest.mark.parametrize("cfg_model", MODELS, ids=lambda x: x[0].name)
+def test_model_save_fold_ln(cfg_model: tuple[ConfigHolder, ZanjHookedTransformer]):
+    cfg: ConfigHolder
+    model: ZanjHookedTransformer
+    cfg, model = cfg_model
+    name: str = cfg.name
+
+    fname: Path = Path(f"tests/_temp/test_model_save-{name}.zanj")
     fname.parent.mkdir(parents=True, exist_ok=True)
     zanj: ZANJ = ZANJ(
         custom_settings={"_load_state_dict_wrapper": {"fold_ln": True}},
     )
-    zanj.save(MODEL, fname)
+    zanj.save(model, fname)
     model_load = zanj.read(fname)
 
-    assert_model_output_equality(MODEL, model_load)
+    assert_model_output_equality(model, model_load)
+
 
+@pytest.mark.parametrize("cfg_model", MODELS, ids=lambda x: x[0].name)
+def test_model_save_refactored_attn_matrices(
+    cfg_model: tuple[ConfigHolder, ZanjHookedTransformer]
+):
+    cfg: ConfigHolder
+    model: ZanjHookedTransformer
+    cfg, model = cfg_model
+    name: str = cfg.name
 
-def test_model_save_refactored_attn_matrices():
-    fname: Path = Path("tests/_temp/test_model_save.zanj")
+    fname: Path = Path(f"tests/_temp/test_model_save-{name}.zanj")
     fname.parent.mkdir(parents=True, exist_ok=True)
     zanj: ZANJ = ZANJ(
         custom_settings={
@@ -73,7 +123,7 @@ def test_model_save_refactored_attn_matrices():
             }
         },
     )
-    zanj.save(MODEL, fname)
+    zanj.save(model, fname)
     model_load = zanj.read(fname)
 
-    assert_model_output_equality(MODEL, model_load)
+    assert_model_output_equality(model, model_load)