diff --git a/pyproject.toml b/pyproject.toml
index 37df946..efa776f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,25 +1,21 @@
 [project]
 name = "chronos-forecasting"
-version = "1.5.2"
+version = "1.5.3"
 authors = [
-  { name="Abdul Fatir Ansari", email="ansarnd@amazon.com" },
-  { name="Lorenzo Stella", email="stellalo@amazon.com" },
-  { name="Caner Turkmen", email="atturkm@amazon.com" },
+  { name = "Abdul Fatir Ansari", email = "ansarnd@amazon.com" },
+  { name = "Lorenzo Stella", email = "stellalo@amazon.com" },
+  { name = "Caner Turkmen", email = "atturkm@amazon.com" },
 ]
 description = "Chronos: Pretrained models for time series forecasting"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.9"
-dependencies = [
-    "torch>=2.0,<3",         # package was tested on 2.2
-    "transformers>=4.48,<5",
-    "accelerate>=0.32,<2",
-]
+dependencies = ["torch>=2.0,<3", "transformers>=4.48,<5", "accelerate>=0.32,<2"]
 classifiers = [
-    "Programming Language :: Python :: 3",
-    "License :: OSI Approved :: Apache Software License",
-    "Operating System :: OS Independent",
-    "Topic :: Scientific/Engineering :: Artificial Intelligence",
+  "Programming Language :: Python :: 3",
+  "License :: OSI Approved :: Apache Software License",
+  "Operating System :: OS Independent",
+  "Topic :: Scientific/Engineering :: Artificial Intelligence",
 ]
 
 [build-system]
@@ -30,10 +26,24 @@ build-backend = "hatchling.build"
 packages = ["src/chronos"]
 
 [project.optional-dependencies]
-test = ["pytest~=8.0", "numpy~=1.21"]
+test = ["pytest~=8.0", "numpy>=1.21,<3"]
 typecheck = ["mypy~=1.9"]
-training = ["gluonts[pro]~=0.15", "numpy~=1.21", "datasets~=2.18", "typer", "typer-config", "joblib", "scikit-learn", "tensorboard"]
-evaluation = ["gluonts[pro]~=0.15", "numpy~=1.21", "datasets~=2.18", "typer"]
+training = [
+  "gluonts[pro]~=0.15",
+  "numpy>=1.21,<3",
+  "datasets>=2.18,<4",
+  "typer",
+  "typer-config",
+  "joblib",
+  "scikit-learn",
+  "tensorboard",
+]
+evaluation = [
+  "gluonts[pro]~=0.15",
+  "numpy>=1.21,<3",
+  "datasets>=2.18,<4",
+  "typer",
+]
 
 [project.urls]
 Homepage = "https://github.com/amazon-science/chronos-forecasting"
@@ -42,3 +52,11 @@ Paper = "https://arxiv.org/abs/2403.07815"
 
 [tool.mypy]
 ignore_missing_imports = true
+
+[tool.ruff]
+line-length = 88
+lint.ignore = [
+  "E501", # Line too long
+  "E731", # Do not assign a `lambda` expression, use a `def`
+  "E722", # Do not use bare `except`
+]
diff --git a/src/chronos/chronos.py b/src/chronos/chronos.py
index 870bfa6..4ffebaa 100644
--- a/src/chronos/chronos.py
+++ b/src/chronos/chronos.py
@@ -302,10 +302,12 @@ class ChronosModel(nn.Module):
             A tensor of encoder embeddings with shape
             (batch_size, sequence_length, d_model).
         """
-        assert (
-            self.config.model_type == "seq2seq"
-        ), "Encoder embeddings are only supported for encoder-decoder models"
-        assert hasattr(self.model, "encoder")
+        assert self.config.model_type == "seq2seq", (
+            "Encoder embeddings are only supported for encoder-decoder models"
+        )
+        assert hasattr(self.model, "encoder") and isinstance(
+            self.model.encoder, nn.Module
+        )
 
         return self.model.encoder(
             input_ids=input_ids, attention_mask=attention_mask
@@ -346,7 +348,7 @@ class ChronosModel(nn.Module):
         if top_p is None:
             top_p = self.config.top_p
 
-        assert hasattr(self.model, "generate")
+        assert callable(getattr(self.model, "generate", None))
 
         preds = self.model.generate(
             input_ids=input_ids,
@@ -362,7 +364,7 @@ class ChronosModel(nn.Module):
                 top_k=top_k,
                 top_p=top_p,
             ),
-        )
+        )  # type: ignore
 
         if self.config.model_type == "seq2seq":
             preds = preds[..., 1:]  # remove the decoder start token
diff --git a/src/chronos/chronos_bolt.py b/src/chronos/chronos_bolt.py
index f099e04..9fa2c69 100644
--- a/src/chronos/chronos_bolt.py
+++ b/src/chronos/chronos_bolt.py
@@ -179,7 +179,6 @@ class ChronosBoltModelForForecasting(T5PreTrainedModel):
         encoder_config = copy.deepcopy(config)
         encoder_config.is_decoder = False
         encoder_config.use_cache = False
-        encoder_config.is_encoder_decoder = False
         self.encoder = T5Stack(encoder_config, self.shared)
 
         self._init_decoder(config)
@@ -381,7 +380,6 @@ class ChronosBoltModelForForecasting(T5PreTrainedModel):
     def _init_decoder(self, config):
         decoder_config = copy.deepcopy(config)
         decoder_config.is_decoder = True
-        decoder_config.is_encoder_decoder = False
         decoder_config.num_layers = config.num_decoder_layers
         self.decoder = T5Stack(decoder_config, self.shared)