readme: ---
  license: mit
  datasets:
  - DarwinAnim8or/grug
  language:
  - en
  pipeline_tag: text-generation
  tags:
  - grug
  - caveman
  - fun
  ---
  
  # GPT-Grug-125m
  A finetuned version of [GPT-Neo-125M](https://huggingface.co/EleutherAI/gpt-neo-125M) on the 'grug' dataset.
  A demo is available [here](https://huggingface.co/spaces/DarwinAnim8or/grug-125m-chat)
  
  # Training Procedure
  This was trained on the 'grug' dataset, using the "HappyTransformers" library on Google Colab.
  This model was trained for 4 epochs with learning rate 1e-2.
  The notebook used to train has been included in this repo.
  
  # Biases & Limitations
  This likely contains the same biases and limitations as the original GPT-Neo-125M that it is based on, and additionally heavy biases from the grug datasets.
  
  # Intended Use
  This model is meant for fun, please do not take anything this caveman says seriously.
  
  # Sample Use
  ```python
  #Import model:
  from happytransformer import HappyGeneration
  happy_gen = HappyGeneration("GPT-NEO", "DarwinAnim8or/gpt-grug-125m")
  
  #Set generation settings:
  from happytransformer import GENSettings
  args_top_k = GENSettings(no_repeat_ngram_size=3, do_sample=True,top_k=50, temperature=0.7, max_length=50, early_stopping=False)
  
  #Generate a response:
  result = happy_gen.generate_text("""Person: "Hello grug"
  Grug: "hello person"
  ###
  Person: "how are you grug"
  Grug: "grug doing ok. grug find many berry. good for tribe."
  ###
  Person: "what does grug think of new spear weapon?"
  Grug: "grug no like new spear weapon. grug stick bigger. spear too small, break easy"
  ###
  Person: "what does grug think of football?"
  Grug: \"""", args=args_top_k)
  
  print(result)
  print(result.text)
  ```