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metadata
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: chill_time
          dtype: string
        - name: cook_time
          dtype: string
        - name: cool_time
          dtype: string
        - name: fry_time
          dtype: string
        - name: marinate_time
          dtype: string
        - name: prep_time
          dtype: string
        - name: rest_time
          dtype: string
        - name: servings
          dtype: string
        - name: soak_time
          dtype: string
        - name: stand_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: 3102556
      num_examples: 2000
  download_size: 1262722
  dataset_size: 3102556
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
tags:
  - food
  - recip
license: mit
task_categories:
  - text-classification
  - text-generation
  - text2text-generation
language:
  - en
pretty_name: All Recipes (sm)
size_categories:
  - 1K<n<10K

all-recipes-xs (2000)

All Recipes dataset (small).

from datasets import load_dataset

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

Alternatively, load with pickle from _frozen.pkl:

import pickle
import requests

r = requests.get("https://huggingface.co/datasets/AWeirdDev/all-recipes-sm/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).

{
    "name": "Dutch … Beef",  # Name of the recipe
    "review": "I found this recipe attached…",  # Subheading 
    "rating": 5.0,  # Overall rating 0 ~ 5
    "meta": {
        # Metadata. May not be present
        "active_time": None,
        "additional_time": None,
        "bake_time": None,
        "chill_time": None,
        "cook_time": "4 hrs 5 mins",
        "cool_time": None,
        "fry_time": None,
        "marinate_time": None,
        "prep_time": "10 mins",
        "rest_time": None,
        "servings": "12",
        "soak_time": None,
        "stand_time": None,
        "total_time": "4 hrs 15 mins",
        "yield": "12 servings"
    },
    "ingredients": [
        {
            "name": "corned beef brisket with spice packet",
            "quanity": "1",
            "unit": "(4 pound)"
        },
        ...
    ],
    "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",
        "Carbs": "16g",
        "Fat": "13g",
        "Protein": "13g"
    },
    "url": "https://www.allrecipes.com/recipe/267704/dutch-oven-crunchy-corned-beef/"
}