README.md

---
language:
- en
license: mit
size_categories:
- n<1K
task_categories:
- text-classification
- text-generation
- text2text-generation
pretty_name: All Recipes (xs)
dataset_info:
  features:
  - name: name
    dtype: string
  - name: review
    dtype: string
  - name: rating
    dtype: float64
  - name: meta
    struct:
    - name: active_time
      dtype: string
    - name: additional_time
      dtype: string
    - name: bake_time
      dtype: string
    - name: cook_time
      dtype: string
    - name: cool_time
      dtype: string
    - name: fry_time
      dtype: string
    - name: prep_time
      dtype: string
    - name: rest_time
      dtype: string
    - name: servings
      dtype: string
    - name: soak_time
      dtype: string
    - name: total_time
      dtype: string
    - name: yield
      dtype: string
  - name: ingredients
    list:
    - name: name
      dtype: string
    - name: quanity
      dtype: string
    - name: unit
      dtype: string
  - name: steps
    sequence: string
  - name: cooks_note
    dtype: string
  - name: editors_note
    dtype: string
  - name: nutrition_facts
    struct:
    - name: Calories
      dtype: string
    - name: Carbs
      dtype: string
    - name: Fat
      dtype: string
    - name: Protein
      dtype: string
  - name: url
    dtype: string
  splits:
  - name: train
    num_bytes: 752412
    num_examples: 500
  download_size: 324455
  dataset_size: 752412
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- food
- recipe
---

# all-recipes-xs (500)

[All Recipes](https://allrecipes.com) dataset (extra small).

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("AWeirdDev/all-recipes-xs")
```

Alternatively, load with `pickle` from `_frozen.pkl`:

```python
import pickle
import requests

r = requests.get("https://huggingface.co/datasets/AWeirdDev/all-recipes-xs/resolve/main/_frozen.pkl")
dataset = pickle.loads(r.content)
```

## Features

**Note:** Empty values are presented as `"unknown"` instead of `None` (normally, unless handled by the 🤗 Datasets library).

```python
{
    "name": "Dutch … Beef",  # Name of the recipe
    "review": "I found this recipe attached…",  # Subheading
    "rating": 5.0,  # Overall rating 0 ~ 5
    "meta": {
        # Metadata. Some keys may not present
        "activate_time": None,
        "additional_time": None,
        "bake_time": None,
        "cool_time": None,
        "fry_time": None,
        "rest_time": None,
        "soak_time": None,
        "prep_time": "10 mins",
        "cook_time": "4 hrs 5 mins",
        "total_time": "4 hrs 15 mins",
        "servings": "12",
        "yield": "12 servings"
    },
    "ingredients": [
        {
            "quanity": "1",
            "unit": "(4 pound)",
            "name": "corned beef brisket with spice packet"
        },
        ...
    ],
    "steps": [
        # Steps (unstripped)
        " Place corned beef brisket…\n",
        " Combine brown sugar,  …\n",
        " Preheat an outdoor grill …\n",
        " Place the coated corned …\n"
    ],
    "cooks_note": "If there is a…",  # Cook's Note (if present)
    "editors_note": "Nutrition data for this…",  # Editor's Note (if present)
    "nutrition_facts": {
        "Calories": "251",
        "Fat": "13g",
        "Carbs": "16g",
        "Protein": "13g"
    },
    "url": "https://www.allrecipes.com/recipe/267704/dutch-oven-crunchy-corned-beef/"
}
```