readme: ---
  license: afl-3.0
  ---
  # Docto Bot
  
  ## Usage (HuggingFace Transformers)
  ```
  pip install -U transformers
  ```
  
  ```python
  import random
  from transformers import AutoTokenizer, AutoModelForCausalLM
  
  tokenizer = AutoTokenizer.from_pretrained("docto/Docto-Bot")
  model = AutoModelForCausalLM.from_pretrained("docto/Docto-Bot")
  special_token = '<|endoftext|>'
  
  prompt_text = 'Question: I am having fever\nAnswer:'
  #prompt_text = f'Question: {userinput}\nAnswer:'
  encoded_prompt = tokenizer.encode(prompt_text,
                                    add_special_tokens = False,
                                    return_tensors = 'pt')
  output_sequences = model.generate(
      input_ids = encoded_prompt,
      max_length = 700,
      temperature = 0.9,
      top_k = 20,
      top_p = 0.9,
      repetition_penalty = 1,
      do_sample = True,
      num_return_sequences = 4
  )
  result = tokenizer.decode(random.choice(output_sequences))
  result = result[result.index("Answer: "):result.index(special_token)]
  print(result[8:])
  ```
  
  ## Training Data
  The Docto-Bot was trained on [Medical Question/Answer dataset](https://github.com/LasseRegin/medical-question-answer-data)