diff --git a/poetry.lock b/poetry.lock
index 37f8dbe..5766a57 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
 [[package]]
 name = "absl-py"
@@ -13,13 +13,13 @@ files = [
 
 [[package]]
 name = "accelerate"
-version = "0.23.0"
+version = "0.31.0"
 description = "Accelerate"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "accelerate-0.23.0-py3-none-any.whl", hash = "sha256:fba5065ff4e7c8f0a39df50785023703cd9bf8388073aa13c6457920f3bc5225"},
-    {file = "accelerate-0.23.0.tar.gz", hash = "sha256:2139d219fa9a37773c4279c9afebe9f681f2f29e85a29b0be8d76257bd8e4abe"},
+    {file = "accelerate-0.31.0-py3-none-any.whl", hash = "sha256:0fc608dc49584f64d04711a39711d73cb0ad4ef3d21cddee7ef2216e29471144"},
+    {file = "accelerate-0.31.0.tar.gz", hash = "sha256:b5199865b26106ccf9205acacbe8e4b3b428ad585e7c472d6a46f6fb75b6c176"},
 ]
 
 [package.dependencies]
@@ -28,17 +28,19 @@ numpy = ">=1.17"
 packaging = ">=20.0"
 psutil = "*"
 pyyaml = "*"
+safetensors = ">=0.3.1"
 torch = ">=1.10.0"
 
 [package.extras]
-dev = ["bitsandbytes", "black (>=23.1,<24.0)", "datasets", "deepspeed", "evaluate", "hf-doc-builder (>=0.3.0)", "parameterized", "pytest", "pytest-subtests", "pytest-xdist", "rich", "ruff (>=0.0.241)", "scikit-learn", "scipy", "timm", "tqdm", "transformers", "urllib3 (<2.0.0)"]
-quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.0.241)", "urllib3 (<2.0.0)"]
+deepspeed = ["deepspeed (<=0.14.0)"]
+dev = ["bitsandbytes", "black (>=23.1,<24.0)", "datasets", "diffusers", "evaluate", "hf-doc-builder (>=0.3.0)", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "rich", "ruff (>=0.2.1,<0.3.0)", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
+quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.2.1,<0.3.0)"]
 rich = ["rich"]
 sagemaker = ["sagemaker"]
-test-dev = ["bitsandbytes", "datasets", "deepspeed", "evaluate", "scikit-learn", "scipy", "timm", "tqdm", "transformers"]
-test-prod = ["parameterized", "pytest", "pytest-subtests", "pytest-xdist"]
-test-trackers = ["comet-ml", "tensorboard", "wandb"]
-testing = ["bitsandbytes", "datasets", "deepspeed", "evaluate", "parameterized", "pytest", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "timm", "tqdm", "transformers"]
+test-dev = ["bitsandbytes", "datasets", "diffusers", "evaluate", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
+test-prod = ["parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist"]
+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 = "aiohttp"
@@ -162,6 +164,30 @@ files = [
 [package.dependencies]
 frozenlist = ">=1.1.0"
 
+[[package]]
+name = "albumentations"
+version = "1.3.1"
+description = "Fast image augmentation library and easy to use wrapper around other libraries"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "albumentations-1.3.1-py3-none-any.whl", hash = "sha256:6b641d13733181d9ecdc29550e6ad580d1bfa9d25e2213a66940062f25e291bd"},
+    {file = "albumentations-1.3.1.tar.gz", hash = "sha256:a6a38388fe546c568071e8c82f414498e86c9ed03c08b58e7a88b31cf7a244c6"},
+]
+
+[package.dependencies]
+numpy = ">=1.11.1"
+opencv-python-headless = ">=4.1.1"
+PyYAML = "*"
+qudida = ">=0.0.4"
+scikit-image = ">=0.16.1"
+scipy = ">=1.1.0"
+
+[package.extras]
+develop = ["imgaug (>=0.4.0)", "pytest"]
+imgaug = ["imgaug (>=0.4.0)"]
+tests = ["pytest"]
+
 [[package]]
 name = "antlr4-python3-runtime"
 version = "4.9.3"
@@ -586,6 +612,23 @@ files = [
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 ]
 
+[[package]]
+name = "coloredlogs"
+version = "15.0.1"
+description = "Colored terminal output for Python's logging module"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+files = [
+    {file = "coloredlogs-15.0.1-py2.py3-none-any.whl", hash = "sha256:612ee75c546f53e92e70049c9dbfcc18c935a2b9a53b66085ce9ef6a6e5c0934"},
+    {file = "coloredlogs-15.0.1.tar.gz", hash = "sha256:7c991aa71a4577af2f82600d8f8f3a89f936baeaf9b50a9c197da014e5bf16b0"},
+]
+
+[package.dependencies]
+humanfriendly = ">=9.1"
+
+[package.extras]
+cron = ["capturer (>=2.4)"]
+
 [[package]]
 name = "comm"
 version = "0.1.4"
@@ -799,6 +842,73 @@ files = [
 docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
 tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
+[[package]]
+name = "cython"
+version = "3.0.10"
+description = "The Cython compiler for writing C extensions in the Python language."
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7"
+files = [
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+]
+
 [[package]]
 name = "debugpy"
 version = "1.8.0"
@@ -850,18 +960,18 @@ files = [
 
 [[package]]
 name = "diffusers"
-version = "0.23.0"
+version = "0.29.0"
 description = "State-of-the-art diffusion in PyTorch and JAX."
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "diffusers-0.23.0-py3-none-any.whl", hash = "sha256:4011e7a29681489e55496350c47ffb940fcfa52771306ae713a5810bf37d6813"},
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+    {file = "diffusers-0.29.0-py3-none-any.whl", hash = "sha256:4c194d2379644a0f7ef9b4ff12c8cf5de4c6324e811265754f08e2f839b8cedb"},
+    {file = "diffusers-0.29.0.tar.gz", hash = "sha256:0212030a8fabe7a07d1c8e925ccdf7a529a98b0425fa078900a679b2451a8ac2"},
 ]
 
 [package.dependencies]
 filelock = "*"
-huggingface-hub = ">=0.13.2"
+huggingface-hub = ">=0.23.2"
 importlib-metadata = "*"
 numpy = "*"
 Pillow = "*"
@@ -870,13 +980,24 @@ requests = "*"
 safetensors = ">=0.3.1"
 
 [package.extras]
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 flax = ["flax (>=0.4.1)", "jax (>=0.4.1)", "jaxlib (>=0.4.1)"]
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+torch = ["accelerate (>=0.29.3)", "torch (>=1.4)"]
+training = ["Jinja2", "accelerate (>=0.29.3)", "datasets", "peft (>=0.6.0)", "protobuf (>=3.20.3,<4)", "tensorboard"]
+
+[[package]]
+name = "easydict"
+version = "1.13"
+description = "Access dict values as attributes (works recursively)."
+optional = false
+python-versions = "*"
+files = [
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+    {file = "easydict-1.13.tar.gz", hash = "sha256:b1135dedbc41c8010e2bc1f77ec9744c7faa42bce1a1c87416791449d6c87780"},
+]
 
 [[package]]
 name = "einops"
@@ -1145,18 +1266,18 @@ tqdm = ["tqdm"]
 
 [[package]]
 name = "huggingface-hub"
-version = "0.17.3"
+version = "0.23.3"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "huggingface_hub-0.17.3-py3-none-any.whl", hash = "sha256:545eb3665f6ac587add946e73984148f2ea5c7877eac2e845549730570c1933a"},
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+    {file = "huggingface_hub-0.23.3-py3-none-any.whl", hash = "sha256:22222c41223f1b7c209ae5511d2d82907325a0e3cdbce5f66949d43c598ff3bc"},
+    {file = "huggingface_hub-0.23.3.tar.gz", hash = "sha256:1a1118a0b3dea3bab6c325d71be16f5ffe441d32f3ac7c348d6875911b694b5b"},
 ]
 
 [package.dependencies]
 filelock = "*"
-fsspec = "*"
+fsspec = ">=2023.5.0"
 packaging = ">=20.9"
 pyyaml = ">=5.1"
 requests = "*"
@@ -1164,17 +1285,32 @@ tqdm = ">=4.42.1"
 typing-extensions = ">=3.7.4.3"
 
 [package.extras]
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-typing = ["pydantic (<2.0)", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
+tensorflow-testing = ["keras (<3.0)", "tensorflow"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
+torch = ["safetensors", "torch"]
+typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
+
+[[package]]
+name = "humanfriendly"
+version = "10.0"
+description = "Human friendly output for text interfaces using Python"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+files = [
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+]
+
+[package.dependencies]
+pyreadline3 = {version = "*", markers = "sys_platform == \"win32\" and python_version >= \"3.8\""}
 
 [[package]]
 name = "idna"
@@ -1237,6 +1373,31 @@ docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker
 perf = ["ipython"]
 testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)", "pytest-ruff"]
 
+[[package]]
+name = "insightface"
+version = "0.7.3"
+description = "InsightFace Python Library"
+optional = false
+python-versions = "*"
+files = [
+    {file = "insightface-0.7.3.tar.gz", hash = "sha256:f191f719612ebb37018f41936814500544cd0f86e6fcd676c023f354c668ddf7"},
+]
+
+[package.dependencies]
+albumentations = "*"
+cython = "*"
+easydict = "*"
+matplotlib = "*"
+numpy = "*"
+onnx = "*"
+Pillow = "*"
+prettytable = "*"
+requests = "*"
+scikit-image = "*"
+scikit-learn = "*"
+scipy = "*"
+tqdm = "*"
+
 [[package]]
 name = "invisible-watermark"
 version = "0.2.0"
@@ -1409,6 +1570,17 @@ MarkupSafe = ">=2.0"
 [package.extras]
 i18n = ["Babel (>=2.7)"]
 
+[[package]]
+name = "joblib"
+version = "1.4.2"
+description = "Lightweight pipelining with Python functions"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "joblib-1.4.2.tar.gz", hash = "sha256:2382c5816b2636fbd20a09e0f4e9dad4736765fdfb7dca582943b9c1366b3f0e"},
+]
+
 [[package]]
 name = "json5"
 version = "0.9.14"
@@ -2331,6 +2503,90 @@ files = [
 antlr4-python3-runtime = "==4.9.*"
 PyYAML = ">=5.1.0"
 
+[[package]]
+name = "onnx"
+version = "1.16.1"
+description = "Open Neural Network Exchange"
+optional = false
+python-versions = ">=3.8"
+files = [
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 version = "4.8.1.78"
@@ -2377,6 +2633,48 @@ numpy = [
     {version = ">=1.23.5", markers = "python_version >= \"3.11\""},
 ]
 
+[[package]]
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+    {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""},
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+]
+
 [[package]]
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 version = "7.4.0"
@@ -2550,6 +2848,35 @@ files = [
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 testing = ["docopt", "pytest (<6.0.0)"]
 
+[[package]]
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+version = "0.11.1"
+description = "Parameter-Efficient Fine-Tuning (PEFT)"
+optional = false
+python-versions = ">=3.8.0"
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+psutil = "*"
+pyyaml = "*"
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+torch = ">=1.13.0"
+tqdm = "*"
+transformers = "*"
+
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+docs-specific = ["black", "hf-doc-builder"]
+quality = ["black", "hf-doc-builder", "ruff (>=0.2.1,<0.3.0)"]
+test = ["black", "datasets", "diffusers (<0.21.0)", "hf-doc-builder", "parameterized", "pytest", "pytest-cov", "pytest-xdist", "ruff (>=0.2.1,<0.3.0)", "scipy"]
+
 [[package]]
 name = "pexpect"
 version = "4.8.0"
@@ -2657,6 +2984,23 @@ files = [
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 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)"]
 
+[[package]]
+name = "prettytable"
+version = "3.10.0"
+description = "A simple Python library for easily displaying tabular data in a visually appealing ASCII table format"
+optional = false
+python-versions = ">=3.8"
+files = [
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+
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+
 [[package]]
 name = "prometheus-client"
 version = "0.17.1"
@@ -2817,6 +3161,17 @@ files = [
 [package.extras]
 diagrams = ["jinja2", "railroad-diagrams"]
 
+[[package]]
+name = "pyreadline3"
+version = "3.4.1"
+description = "A python implementation of GNU readline."
+optional = false
+python-versions = "*"
+files = [
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+]
+
 [[package]]
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 version = "2.8.2"
@@ -2984,6 +3339,7 @@ files = [
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@@ -3123,6 +3479,23 @@ files = [
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 cffi = {version = "*", markers = "implementation_name == \"pypy\""}
 
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+description = "QUick and DIrty Domain Adaptation"
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+typing-extensions = "*"
+
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@@ -3391,82 +3764,125 @@ files = [
 
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@@ -3748,6 +4209,17 @@ files = [
 [package.dependencies]
 torch = "*"
 
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@@ -3803,118 +4275,120 @@ test = ["flake8", "isort", "pytest"]
 
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+integrations = ["optuna", "ray[tune] (>=2.7.0)", "sigopt"]
 ja = ["fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "rhoknp (>=1.1.0,<1.3.1)", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"]
 modelcreation = ["cookiecutter (==1.7.3)"]
-natten = ["natten (>=0.14.6)"]
+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)", "black (>=23.1,<24.0)", "datasets (!=2.5.0)", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)", "ruff (>=0.0.241,<=0.0.259)", "urllib3 (<2.0.0)"]
-ray = ["ray[tune]"]
+quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "ruff (==0.1.5)", "urllib3 (<2.0.0)"]
+ray = ["ray[tune] (>=2.7.0)"]
 retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
 sagemaker = ["sagemaker (>=2.31.0)"]
 sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
-serving = ["fastapi", "pydantic (<2)", "starlette", "uvicorn"]
+serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
 sigopt = ["sigopt"]
 sklearn = ["scikit-learn"]
 speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
-testing = ["GitPython (<3.1.19)", "beautifulsoup4", "black (>=23.1,<24.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "parameterized", "protobuf", "psutil", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "timeout-decorator"]
-tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>=2.6,<2.15)", "tensorflow-text (<2.15)", "tf2onnx"]
-tf-cpu = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>=2.6,<2.15)", "tensorflow-text (<2.15)", "tf2onnx"]
+testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "parameterized", "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 (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
+tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
+tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
 tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 timm = ["timm"]
-tokenizers = ["tokenizers (>=0.14,<0.15)"]
-torch = ["accelerate (>=0.20.3)", "torch (>=1.10,!=1.12.0)"]
+tokenizers = ["tokenizers (>=0.19,<0.20)"]
+torch = ["accelerate (>=0.21.0)", "torch"]
 torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
-torch-vision = ["Pillow (<10.0.0)", "torchvision"]
-torchhub = ["filelock", "huggingface-hub (>=0.16.4,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.14,<0.15)", "torch (>=1.10,!=1.12.0)", "tqdm (>=4.27)"]
+torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
+torchhub = ["filelock", "huggingface-hub (>=0.23.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"]
 video = ["av (==9.2.0)", "decord (==0.6.0)"]
-vision = ["Pillow (<10.0.0)"]
+vision = ["Pillow (>=10.0.1,<=15.0)"]
 
 [[package]]
 name = "triton"
@@ -4463,4 +4961,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "4640f925df1102f0560ca8ac6dbaf55bd9368fdded5b5e3c94901c8ef4b9a956"
+content-hash = "efe3f385cdce67877df7018b7eeb79e52a4af03253e41be9c3dbe06f1124a7fc"
diff --git a/pyproject.toml b/pyproject.toml
index a7eb84d..d8b243c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,8 +14,8 @@ omegaconf = "2.3.0"
 diffusers = "0.29.0"
 compel = "2.0.2"
 invisible-watermark = "^0.2.0"
-transformers = "^4.41.1"
-accelerate = "^0.23.0"
+transformers = "^4.41.2"
+accelerate = "^0.31.0"
 safetensors = "0.4.3"
 mediapy = "^1.1.9"
 ipywidgets = "7.7.1"
diff --git a/stablepy/__init__.py b/stablepy/__init__.py
index e66d731..108ff01 100644
--- a/stablepy/__init__.py
+++ b/stablepy/__init__.py
@@ -16,4 +16,6 @@
     IP_ADAPTERS_SDXL,
     REPO_IMAGE_ENCODER,
     ALL_PROMPT_WEIGHT_OPTIONS,
+    SD15_TASKS,
+    SDXL_TASKS,
 )
diff --git a/stablepy/diffusers_vanilla/constants.py b/stablepy/diffusers_vanilla/constants.py
index 36b00ee..d0e0f6a 100644
--- a/stablepy/diffusers_vanilla/constants.py
+++ b/stablepy/diffusers_vanilla/constants.py
@@ -39,14 +39,23 @@
     "sdxl_lineart_t2i": "TencentARC/t2i-adapter-lineart-sdxl-1.0",
     "sdxl_depth-midas_t2i": "TencentARC/t2i-adapter-depth-midas-sdxl-1.0",
     "sdxl_openpose_t2i": "TencentARC/t2i-adapter-openpose-sdxl-1.0",
-    # "sdxl_depth-zoe_t2i": "TencentARC/t2i-adapter-depth-zoe-sdxl-1.0",
-    # "sdxl_recolor_t2i": "TencentARC/t2i-adapter-recolor-sdxl-1.0",
     "img2img": "Nothinghere",
     "pattern": ["monster-labs/control_v1p_sd15_qrcode_monster", "r3gm/control_v1p_sdxl_qrcode_monster_fp16"],
     "sdxl_tile_realistic": "Yakonrus/SDXL_Controlnet_Tile_Realistic_v2",
+    # "sdxl_depth-zoe_t2i": "TencentARC/t2i-adapter-depth-zoe-sdxl-1.0",
+    # "sdxl_recolor_t2i": "TencentARC/t2i-adapter-recolor-sdxl-1.0",
 }
 
 VALID_TASKS = list(CONTROLNET_MODEL_IDS.keys())
+SD15_TASKS = [x for x in VALID_TASKS if ("sdxl" not in x.lower())]
+SDXL_TASKS = [
+    y for y in VALID_TASKS
+    if (
+        "sdxl" in y.lower()
+        or isinstance(CONTROLNET_MODEL_IDS[y], list)
+        or y in ["txt2img", "img2img", "inpaint"]
+    )
+]
 
 T2I_PREPROCESSOR_NAME = {
     "sdxl_canny_t2i": "Canny",
diff --git a/stablepy/diffusers_vanilla/model.py b/stablepy/diffusers_vanilla/model.py
index bbd09a8..b7164f4 100644
--- a/stablepy/diffusers_vanilla/model.py
+++ b/stablepy/diffusers_vanilla/model.py
@@ -43,6 +43,8 @@
 from .constants import (
     CONTROLNET_MODEL_IDS,
     VALID_TASKS,
+    SD15_TASKS,
+    SDXL_TASKS,
     T2I_PREPROCESSOR_NAME,
     FLASH_LORA,
     SCHEDULER_CONFIG_MAP,
@@ -475,6 +477,11 @@ def load_pipe(
             self.pipe.watermark = None
             return
 
+        # if class_name == "StableDiffusionPipeline" and task_name not in SD15_TASKS:
+        #     logger.error(f"The selected task: {task_name} is not implemented for SD 1.5")
+        # elif class_name == "StableDiffusionXLPipeline" and task_name not in SDXL_TASKS:
+        #     logger.error(f"The selected task: {task_name} is not implemented for SDXL")
+
         # Load task
         model_id = CONTROLNET_MODEL_IDS[task_name]
         if isinstance(model_id, list):
@@ -786,10 +793,14 @@ def process_inpaint(
             # Convert control image to draw
             import base64
             import matplotlib.pyplot as plt
-            name_without_extension = os.path.splitext(image.split("/")[-1])[0]
-            image64 = base64.b64encode(open(image, "rb").read())
+
+            Image.fromarray(image).save("inpaint_image.png")
+            image_aux = "./inpaint_image.png"
+
+            name_without_extension = os.path.splitext(image_aux.split("/")[-1])[0]
+            image64 = base64.b64encode(open(image_aux, "rb").read())
             image64 = image64.decode("utf-8")
-            img = np.array(plt.imread(f"{image}")[:, :, :3])
+            img = np.array(plt.imread(f"{image_aux}")[:, :, :3])
 
             # Create mask interactive
             logger.info("Draw the mask on this canvas using the mouse. When you finish, press 'Finish' in the bottom side of the canvas.")
@@ -1077,7 +1088,8 @@ def process_lora(self, select_lora, lora_weights_scale, unload=False):
                     )
                     logger.info(select_lora)
                 except Exception as e:
-                    traceback.print_exc()
+                    if logger.isEnabledFor(logging.DEBUG):
+                        traceback.print_exc()
                     logger.error(f"ERROR: LoRA not compatible: {select_lora}")
                     logger.debug(f"{str(e)}")
             return self.pipe
@@ -1102,10 +1114,14 @@ def load_style_file(self, style_json_file):
         if os.path.exists(style_json_file):
             try:
                 file_json_read = get_json_content(style_json_file)
-                self.styles_data = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in file_json_read}
+                self.styles_data = {
+                    k["name"]: (k["prompt"], k["negative_prompt"] if "negative_prompt" in k else "") for k in file_json_read
+                }
                 self.STYLE_NAMES = list(self.styles_data.keys())
                 self.style_json_file = style_json_file
-                logger.info(f"Styles json file loaded with {len(self.STYLE_NAMES)} styles")
+                logger.info(
+                    f"Styles json file loaded with {len(self.STYLE_NAMES)} styles"
+                )
                 logger.debug(str(self.STYLE_NAMES))
             except Exception as e:
                 logger.error(str(e))
@@ -1115,7 +1131,9 @@ def load_style_file(self, style_json_file):
     def load_beta_styles(self):
         from .constants import BETA_STYLE_LIST
 
-        styles_data = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in BETA_STYLE_LIST}
+        styles_data = {
+            k["name"]: (k["prompt"], k["negative_prompt"] if "negative_prompt" in k else "") for k in BETA_STYLE_LIST
+        }
         STYLE_NAMES = list(styles_data.keys())
         self.styles_data = styles_data
         self.STYLE_NAMES = STYLE_NAMES
@@ -1411,11 +1429,22 @@ def __call__(
             seed (int, optional, defaults to -1):
                 A seed for controlling the randomness of the image generation process. -1 design a random seed.
             sampler (str, optional, defaults to "DPM++ 2M"):
-                The sampler used for the generation process. Available samplers: DPM++ 2M, DPM++ 2M Karras, DPM++ 2M SDE,
-                DPM++ 2M SDE Karras, DPM++ SDE, DPM++ SDE Karras, DPM2, DPM2 Karras, Euler, Euler a, Heun, LMS, LMS Karras,
-                DDIM, DEIS, UniPC, DPM2 a, DPM2 a Karras, PNDM, TCD, LCM, DPM++ 2M Lu, DPM++ 2M Ef, DPM++ 2M SDE Lu and DPM++ 2M SDE Ef.
+                The sampler used for the generation process.
+                To see all the valid sampler names, use the following code:
+
+                ```python
+                from stablepy import scheduler_names
+                print(scheduler_names)
+                ```
             syntax_weights (str, optional, defaults to "Classic"):
-                Specifies the type of syntax weights used during generation. "Classic" is (word:weight), "Compel" is (word)weight
+                Specifies the type of syntax weights and emphasis used during generation. 
+                "Classic" is (word:weight), "Compel" is (word)weight.
+                To see all the valid syntax weight options, use the following code:
+
+                ```python
+                from stablepy import ALL_PROMPT_WEIGHT_OPTIONS
+                print(ALL_PROMPT_WEIGHT_OPTIONS)
+                ```
             lora_A (str, optional):
                 Placeholder for lora A parameter.
             lora_scale_A (float, optional, defaults to 1.0):
@@ -1546,6 +1575,28 @@ def __call__(
                 The previous adetailer model remains preloaded in memory.
             retain_hires_model_previous_load (bool, optional, defaults to False):
                 The previous hires model remains preloaded in memory.
+            ip_adapter_image (Optional[Any], optional, default=[]):
+                Image path or list of image paths for ip adapter.
+            ip_adapter_mask (Optional[Any], optional, default=[]):
+                Mask image path or list of mask image paths for ip adapter.
+            ip_adapter_model (Optional[Any], optional, default=[]):
+                Adapter model name or list of adapter model names.
+
+                To see all the valid model names for SD1.5:
+                ```python
+                from stablepy import IP_ADAPTERS_SD
+                print(IP_ADAPTERS_SD)
+                ```
+
+                To see all the valid model names for SDXL:
+                ```python
+                from stablepy import IP_ADAPTERS_SDXL
+                print(IP_ADAPTERS_SDXL)
+                ```
+            ip_adapter_scale (Optional[Any], optional, default=[1.0]):
+                Scaling factor or list of scaling factors for the ip adapter models.
+            ip_adapter_mode (Optional[Any], optional, default=['original']):
+                Adapter mode or list of adapter modes. Possible values are 'original', 'style', 'layout', 'style+layout'.
             image_previews (bool, optional, defaults to False):
                 Displaying the image denoising process.
             xformers_memory_efficient_attention (bool, optional, defaults to False):
@@ -1570,7 +1621,7 @@ def __call__(
                 - image_resolution
                 - strength
 
-            Additional parameters that will be used in ControlNet for SD 1.5 depending on the task:
+            Additional parameters that will be used in ControlNet for SD 1.5 and SDXL depending on the task:
                 - image
                 - preprocessor_name
                 - preprocess_resolution
@@ -1595,6 +1646,8 @@ def __call__(
 
         """
 
+        if not seed:
+            seed = -1
         if self.task_name != "txt2img" and image is None:
             raise ValueError(
                 "You need to specify the <image> for this task."