readme: 
  ---
  language:
  - en
  tags:
  - text2text-generation
  - paraphrase-generation
  license: apache-2.0
  widget:
   - text: "headline: weight loss"
  ---
  
  ### About the model
  
  The model has been trained on [a dataset containing 138927 article titles](https://www.englishvoice.ai/p/keywords-and-titles/ "a dataset containing 138927 article titles") along with their keywords.
  
  The purpose of the model is to generate suggestions of article headlines, given a keyword or multiple keywords.
  
  ### Generation examples
  
  | Input | Output |
  | :------------ | :------------ |
  | weight loss  | The Last Weight Loss Plan: Lose Weight, Feel Great, and Get in Shape <br/>How to Lose Weight Without Giving Up Your Favorite Foods <br/> I Lost Weight and Finally Feel Good About My Body |
  | property rental, property management | Property rental: The new way to make money <br/> We take the hassle out of property rental <br/> Is property management your new best friend? |
  | diabetic diet plan | A diabetic diet plan that actually works! <br/> Lose weight, feel great, and live better with our diabetic diet plan! <br/> Diet has never been so tasty: Our diabetic diet plan puts you to the test! |
  
  You can supply multiple keywords by separating them with commas. Higher temperature settings result in more creative headlines; we recommend testing first with the temperature set to 1.5.
  
  
  ### The dataset
  
  The dataset was developed by English Voice AI Labs. You can download it from our website:
  [https://www.EnglishVoice.ai/](https://www.EnglishVoice.ai/ "https://www.EnglishVoice.ai/")
  
  ### Sample code
  
  Python code for generating headlines:
  
  ```python
  import torch
  from transformers import T5ForConditionalGeneration,T5Tokenizer
  
  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
  
  model = T5ForConditionalGeneration.from_pretrained("EnglishVoice/t5-base-keywords-to-headline")
  tokenizer = T5Tokenizer.from_pretrained("EnglishVoice/t5-base-keywords-to-headline")
  model = model.to(device)
  
  keywords = "weight loss, weight pills"
  
  text =  "headline: " + keywords
  encoding = tokenizer.encode_plus(text, return_tensors = "pt")
  input_ids = encoding["input_ids"].to(device)
  attention_masks = encoding["attention_mask"].to(device)
  beam_outputs = model.generate(
      input_ids = input_ids,
      attention_mask = attention_masks,
      do_sample = True,
      num_return_sequences = 5,
      temperature = 0.95,
      early_stopping = True,
      top_k = 50,
      top_p = 0.95,
  )
  
  for i in range(len(beam_outputs)):
      result = tokenizer.decode(beam_outputs[i], skip_special_tokens=True)
      print(result)
  ```
  
  Sample result:
  
      I Am Losing Weight and I Love It!
      New Weight Loss Pill Helps You Get the Body You Want!
      I Lost Weight By Taking Pills!
      The Truth About Weight Loss Pills!
      The Best Weight Loss Pills Money Can Buy!
  