diff --git a/docs/advanced/decimal.md b/docs/advanced/decimal.md
index 26994eccf8..ce971b201b 100644
--- a/docs/advanced/decimal.md
+++ b/docs/advanced/decimal.md
@@ -33,45 +33,7 @@ For the database, **SQLModel** will use <a href="https://docs.sqlalchemy.org/en/
 
 Let's say that each hero in the database will have an amount of money. We could make that field a `Decimal` type using the `condecimal()` function:
 
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-```python hl_lines="11"
-{!./docs_src/advanced/decimal/tutorial001_py310.py[ln:1-11]!}
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-# More code here later 👇
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-```python hl_lines="12"
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-```Python
-{!./docs_src/advanced/decimal/tutorial001_py310.py!}
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-```Python
-{!./docs_src/advanced/decimal/tutorial001.py!}
-```
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+{* ./docs_src/advanced/decimal/tutorial001_py310.py ln[1:11] hl[11] *}
 
 Here we are saying that `money` can have at most `5` digits with `max_digits`, **this includes the integers** (to the left of the decimal dot) **and the decimals** (to the right of the decimal dot).
 
@@ -105,97 +67,13 @@ Make sure you adjust the number of digits and decimal places for your own needs,
 
 When creating new models you can actually pass normal (`float`) numbers, Pydantic will automatically convert them to `Decimal` types, and **SQLModel** will store them as `Decimal` types in the database (using SQLAlchemy).
 
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-```Python
-{!./docs_src/advanced/decimal/tutorial001_py310.py!}
-```
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-```Python
-{!./docs_src/advanced/decimal/tutorial001.py!}
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+{* ./docs_src/advanced/decimal/tutorial001_py310.py ln[24:34] hl[25:27] *}
 
 ## Select Decimal data
 
 Then, when working with Decimal types, you can confirm that they indeed avoid those rounding errors from floats:
 
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-```Python hl_lines="15-16"
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-```Python hl_lines="15-16"
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-# Code below omitted 👇
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-```Python
-{!./docs_src/advanced/decimal/tutorial001_py310.py!}
-```
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-```Python
-{!./docs_src/advanced/decimal/tutorial001.py!}
-```
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+{* ./docs_src/advanced/decimal/tutorial001_py310.py ln[37:50] hl[49:50] *}
 
 ## Review the results