readme: ---
  
  language: en
  
  tags:
  
  - ELI5
  
  license:  	gpl-3.0
  
  datasets:
  - eli5
  
  Task: Summarization
  
  widget:
  - text: "<|BOS|><|SEP|>Consulting,business,Fraud<|SEP|>"
  
  inference:
    parameters:
      temperature: 0.9
      return_full_text: False
      repetition_penalty: 1
  ---
  # Conditional ELI5 Generator
  
  Given a few keywords, it generates an Eli5 question with a corresponding answer.
  
  The model is mainly used for [SeemsPhishy](https://github.com/madhour/seemsphishy) to auto generate newsletters for phishing/penetration-testing.
  
  # How to use
  
  ```Python
  from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
  from torch import tensor
  
  tokenizer = AutoTokenizer.from_pretrained("Madhour/gpt2-eli5")
  model = AutoModelForCausalLM.from_pretrained("Madhour/gpt2-eli5")
  prompt = <|BOS|> +"I have a question."+ <|SEP|> + "keyword1,keyword2,keyword3" + <|SEP|>
  prompt = tensor(tokenizer.encode(prompt)).unsqueeze(0)
  text = model.generate(prompt, 
                              do_sample=True,   
                              min_length=50, 
                              max_length=768,
                              top_k=30,                                 
                              top_p=0.7,        
                              temperature=0.9,
                              repetition_penalty=2.0,
                              num_return_sequences=3)
  ```