diff --git a/docs/features/quantization/fp8.md b/docs/features/quantization/fp8.md
index 0c5111fb8af0d..d4a6176b236f1 100644
--- a/docs/features/quantization/fp8.md
+++ b/docs/features/quantization/fp8.md
@@ -60,7 +60,7 @@ Since simple RTN does not require data for weight quantization and the activatio
 ??? code
 
     ```python
-    from llmcompressor.transformers import oneshot
+    from llmcompressor import oneshot
     from llmcompressor.modifiers.quantization import QuantizationModifier
 
     # Configure the simple PTQ quantization
diff --git a/docs/features/quantization/int4.md b/docs/features/quantization/int4.md
index 035e7ea291f9e..9752039097d63 100644
--- a/docs/features/quantization/int4.md
+++ b/docs/features/quantization/int4.md
@@ -80,7 +80,7 @@ Now, apply the quantization algorithms:
 ??? code
 
     ```python
-    from llmcompressor.transformers import oneshot
+    from llmcompressor import oneshot
     from llmcompressor.modifiers.quantization import GPTQModifier
     from llmcompressor.modifiers.smoothquant import SmoothQuantModifier
 
diff --git a/docs/features/quantization/int8.md b/docs/features/quantization/int8.md
index ec8a77f74ffef..701ca6378cb16 100644
--- a/docs/features/quantization/int8.md
+++ b/docs/features/quantization/int8.md
@@ -87,7 +87,7 @@ Now, apply the quantization algorithms:
 ??? code
 
     ```python
-    from llmcompressor.transformers import oneshot
+    from llmcompressor import oneshot
     from llmcompressor.modifiers.quantization import GPTQModifier
     from llmcompressor.modifiers.smoothquant import SmoothQuantModifier
 
diff --git a/docs/features/quantization/quantized_kvcache.md b/docs/features/quantization/quantized_kvcache.md
index 56cf057678be6..d26a5e217f314 100644
--- a/docs/features/quantization/quantized_kvcache.md
+++ b/docs/features/quantization/quantized_kvcache.md
@@ -78,7 +78,7 @@ Here's a complete example using `meta-llama/Llama-3.1-8B-Instruct` (most models
     ```python
     from datasets import load_dataset
     from transformers import AutoModelForCausalLM, AutoTokenizer
-    from llmcompressor.transformers import oneshot
+    from llmcompressor import oneshot
 
     # Select model and load it
     MODEL_ID = "meta-llama/Llama-3.1-8B-Instruct"