diff --git a/eland/ml/pytorch/__init__.py b/eland/ml/pytorch/__init__.py
index 5f063af3..109d4a3e 100644
--- a/eland/ml/pytorch/__init__.py
+++ b/eland/ml/pytorch/__init__.py
@@ -20,6 +20,7 @@
     FillMaskInferenceOptions,
     NerInferenceOptions,
     NlpBertTokenizationConfig,
+    NlpDebertaV2TokenizationConfig,
     NlpMPNetTokenizationConfig,
     NlpRobertaTokenizationConfig,
     NlpTrainedModelConfig,
@@ -27,6 +28,7 @@
     QuestionAnsweringInferenceOptions,
     TextClassificationInferenceOptions,
     TextEmbeddingInferenceOptions,
+    TextExpansionInferenceOptions,
     TextSimilarityInferenceOptions,
     ZeroShotClassificationInferenceOptions,
 )
@@ -43,12 +45,14 @@
     "NerInferenceOptions",
     "NlpTrainedModelConfig",
     "NlpBertTokenizationConfig",
+    "NlpDebertaV2TokenizationConfig",
     "NlpRobertaTokenizationConfig",
     "NlpXLMRobertaTokenizationConfig",
     "NlpMPNetTokenizationConfig",
     "QuestionAnsweringInferenceOptions",
     "TextClassificationInferenceOptions",
     "TextEmbeddingInferenceOptions",
+    "TextExpansionInferenceOptions",
     "TextSimilarityInferenceOptions",
     "ZeroShotClassificationInferenceOptions",
     "task_type_from_model_config",
diff --git a/eland/ml/pytorch/nlp_ml_model.py b/eland/ml/pytorch/nlp_ml_model.py
index eddd39b7..d848afe7 100644
--- a/eland/ml/pytorch/nlp_ml_model.py
+++ b/eland/ml/pytorch/nlp_ml_model.py
@@ -315,10 +315,12 @@ def __init__(
         *,
         tokenization: NlpTokenizationConfig,
         results_field: t.Optional[str] = None,
+        expansion_type: t.Optional[str] = "elser",
     ):
         super().__init__(configuration_type="text_expansion")
         self.tokenization = tokenization
         self.results_field = results_field
+        self.expansion_type = expansion_type
 
 
 class TrainedModelInput:
diff --git a/eland/ml/pytorch/transformers.py b/eland/ml/pytorch/transformers.py
index 04d4ba86..101e0f22 100644
--- a/eland/ml/pytorch/transformers.py
+++ b/eland/ml/pytorch/transformers.py
@@ -32,7 +32,6 @@
 from torch import Tensor
 from torch.profiler import profile  # type: ignore
 from transformers import (
-    BertTokenizer,
     PretrainedConfig,
     PreTrainedModel,
     PreTrainedTokenizer,
@@ -509,7 +508,10 @@ def _find_max_sequence_length(self) -> int:
                 if max_len is not None and max_len < REASONABLE_MAX_LENGTH:
                     return int(max_len)
 
-        if isinstance(self._tokenizer, BertTokenizer):
+        # Known max input sizes for some tokenizers
+        if isinstance(self._tokenizer, transformers.BertTokenizer):
+            return 512
+        if isinstance(self._tokenizer, transformers.DebertaV2Tokenizer):
             return 512
 
         raise UnknownModelInputSizeError("Cannot determine model max input length")
@@ -552,6 +554,22 @@ def _create_config(
                     tokenization=tokenization_config,
                     embedding_size=embedding_size,
                 )
+        elif self._task_type == "text_expansion" and es_version >= (9, 2, 0):
+            sample_embedding = self._traceable_model.sample_output()
+            if type(sample_embedding) is tuple:
+                text_embedding = sample_embedding[0]
+            else:
+                text_embedding = sample_embedding
+            shape = text_embedding.shape
+            token_window = shape[1]
+            if token_window > 1:
+                expansion_type = "splade"
+            else:
+                expansion_type = "elser" 
+            inference_config = TASK_TYPE_TO_INFERENCE_CONFIG[self._task_type](
+                tokenization=tokenization_config,
+                expansion_type=expansion_type,
+            )
         else:
             inference_config = TASK_TYPE_TO_INFERENCE_CONFIG[self._task_type](
                 tokenization=tokenization_config
diff --git a/tests/ml/pytorch/test_pytorch_model_config_pytest.py b/tests/ml/pytorch/test_pytorch_model_config_pytest.py
index aa141eac..7a45ee71 100644
--- a/tests/ml/pytorch/test_pytorch_model_config_pytest.py
+++ b/tests/ml/pytorch/test_pytorch_model_config_pytest.py
@@ -19,13 +19,6 @@
 
 import pytest
 
-try:
-    import sklearn  # noqa: F401
-
-    HAS_SKLEARN = True
-except ImportError:
-    HAS_SKLEARN = False
-
 try:
     from eland.ml.pytorch.transformers import TransformerModel
 
@@ -46,6 +39,7 @@
         QuestionAnsweringInferenceOptions,
         TextClassificationInferenceOptions,
         TextEmbeddingInferenceOptions,
+        TextExpansionInferenceOptions,
         TextSimilarityInferenceOptions,
         ZeroShotClassificationInferenceOptions,
     )
@@ -54,13 +48,9 @@
 except ImportError:
     HAS_PYTORCH = False
 
-
 from tests import ES_VERSION
 
 pytestmark = [
-    pytest.mark.skipif(
-        not HAS_SKLEARN, reason="This test requires 'scikit-learn' package to run"
-    ),
     pytest.mark.skipif(
         not HAS_TRANSFORMERS, reason="This test requires 'transformers' package to run"
     ),
@@ -70,9 +60,9 @@
 ]
 
 # If the required imports are missing the test will be skipped.
-# Only define th test configurations if the referenced classes
+# Only define the test configurations if the referenced classes
 # have been imported
-if HAS_PYTORCH and HAS_SKLEARN and HAS_TRANSFORMERS:
+if HAS_PYTORCH and HAS_TRANSFORMERS:
     MODEL_CONFIGURATIONS = [
         (
             "sentence-transformers/all-distilroberta-v1",
@@ -154,6 +144,14 @@
             512,
             None,
         ),
+        (
+            "naver/splade-v3-distilbert",
+            "text_expansion",
+            TextExpansionInferenceOptions,
+            NlpBertTokenizationConfig,
+            512,
+            None,
+        ),
     ]
 else:
     MODEL_CONFIGURATIONS = []
@@ -216,6 +214,9 @@ def test_model_config(
             if task_type == "text_similarity":
                 assert tokenization.truncate == "second"
 
+            if task_type == "text_expansion":
+                assert config.inference_config.expansion_type == "splade"
+
             del tm
 
     def test_model_config_with_prefix_string(self):