readme: ---
  language:
  - en
  tags:
  - text generation
  - pytorch
  - causal-lm
  license: apache-2.0
  datasets:
  - custom
  widget:
  - text: "style: Pilsner\nbatch_size: 20\nefficiency: 75\nboil_size:"
    example_title: "Pilsener"
  - text: "style: IPA\nbatch_size: 20\nefficiency: 75\nboil_size:"
    example_title: "IPA"
  - text: "style: Scottish Ale\nbatch_size: 20\nefficiency: 75\nboil_size:"
    example_title: "Scottish Ale"
  inference:
    parameters:
      do_sample: true
      top_k: 10
      top_p: 0.99
      max_length: 500
  ---
  
  # GPT-Neo 125M finetuned with beer recipes
  
  ## Model Description
  
  GPT-Neo 125M is a transformer model based on EleutherAI's replication of the GPT-3 architecture https://huggingface.co/EleutherAI/gpt-neo-125M.
  It generates recipes for brewing beer in a YAML-like format which can be easily used for different purposes.
  
  ## Training data
  
  This model was trained on a custom dataset of ~ 76,800 beer recipes from the internet. It includes recipes for the following 
  styles of beer:
  
  * Strong American Ale 
  * Pale American Ale
  * India Pale Ale (IPA)
  * Standard American Beer
  * Stout
  * English Pale Ale
  * IPA
  * American Porter and Stout
  * Sour Ale
  * Irish Beer
  * Strong British Ale
  * Belgian and French Ale
  * German Wheat and Rye Beer
  * Czech Lager
  * Spice/Herb/Vegetable Beer
  * Specialty Beer
  * American Ale
  * Pilsner
  * Belgian Ale
  * Strong Belgian Ale
  * Bock
  * Brown British Beer
  * German Wheat Beer
  * Fruit Beer
  * Amber Malty European Lager
  * Pale Malty European Lager
  * British Bitter
  * Amber and Brown American Beer
  * Light Hybrid Beer
  * Pale Commonwealth Beer
  * American Wild Ale
  * European Amber Lager
  * Belgian Strong Ale
  * International Lager
  * Amber Bitter European Lager
  * Light Lager
  * Scottish and Irish Ale
  * European Sour Ale
  * Trappist Ale
  * Strong European Beer
  * Porter
  * Historical Beer
  * Pale Bitter European Beer
  * Amber Hybrid Beer
  * Smoke Flavored/Wood-Aged Beer
  * Spiced Beer
  * Dark European Lager
  * Alternative Fermentables Beer
  * Mead
  * Strong Ale
  * Dark British Beer
  * Scottish Ale
  * Smoked Beer
  * English Brown Ale
  * Dark Lager
  * Cider or Perry
  * Wood Beer
  
  ### How to use
  
  You can use this model directly with a pipeline for text generation. This example generates a different recipe each time it's run:
  
  ```py
  >>> from transformers import pipeline
  >>> generator = pipeline('text-generation', model='b3ck1/gpt-neo-125M-finetuned-beer-recipes')
  >>> generator("style: Pilsner\nbatch_size: 20\nefficiency: 75\nboil_size:", do_sample=True, min_length=50, max_length=500)
  >>> print(output[0]['generated_text'])
  
  style: Pilsner
  batch_size: 20
  efficiency: 70
  boil_size: 24
  boil_time: 60
  fermentables:
  - name: Pale Ale
    type: Grain
    amount: 6.5
  hops:
  - name: Saaz
    alpha: 3.5
    use: Boil
    time: 60
    amount: 0.06
  - name: Saaz
    alpha: 3.5
    use: Boil
    time: 30
    amount: 0.06
  - name: Saaz
    alpha: 3.5
    use: Boil
    time: 10
    amount: 0.06
  - name: Saaz
    alpha: 3.5
    use: Boil
    time: 0
    amount: 0.06
  yeasts:
  - name: Safale - American Ale Yeast US-05
    amount: 0.11
    min_temperature: 12
    max_temperature: 25
  primary_temp: null
  mash_steps:
  - step_temp: 65
    step_time: 60
  miscs: []
  ```
  
  ### See this model in action
  
  This model was used to build https://beerai.net.