Describe where the data comes from

README.md

@@ -17,3 +17,52 @@ configs:
   - split: train
     path: data/train-*
 ---
+
+This is a simple recipes dataset, obtained by formatting/cleaning [this one](formido/recipes-20k), that I think it was just made by scrapping the food.com website. 
+Here's the cleanup script I used to obtain it.
+
+```python
+from datasets import load_dataset
+
+def clean_recipe(recipe):
+    recipe = recipe.replace(" , ", ", ")
+    recipe = recipe.replace('"', "'")
+    recipe = recipe.replace("\\'", "'")
+    recipe = recipe.strip("\\']")
+    recipe = recipe.strip("['")
+    splitted = recipe.split("\', \'")
+    recipe = "\n".join(map(lambda x: "- " + (x.capitalize()), splitted))
+    return recipe
+
+def clean_name(name):
+    name = name.capitalize()
+    name = name.replace("  ", " ")
+    return name
+
+def preprocess_function(examples):
+    recipes = examples["output"]
+    names = examples["input"]
+
+    clean_recipes = []
+    clean_names = []
+    for recipe, name in zip(recipes, names):
+        # Sanitize the name and recipe string
+        clean_recipes.append(clean_recipe(recipe))
+        clean_names.append(clean_name(name))
+
+    return {"recipes": clean_recipes, "names": clean_names}
+
+def split_dataset():
+    from transformers import set_seed
+    set_seed(42)
+    dataset_id = "formido/recipes-20k"
+    dataset = load_dataset(dataset_id)
+    dataset = dataset.map(preprocess_function, batched=True, remove_columns=dataset["train"].column_names)
+    dataset.push_to_hub("simple_recipes")
+
+
+if __name__ == "__main__":
+    split_dataset()
+
+```
+