readme: ---
  language: ["es"]
  tags:
  - spanish
  - question generation
  - qg
  Datasets:
  - SQUAD
  license: mit
  ---
  This is the finetuned model of hiiamsid/est5-base for Question Generation task.
  * Here input is the context only and output is questions. No information regarding answers were given to model. 
  * Unfortunately, due to lack of sufficient resources it is fine tuned with batch_size=10 and num_seq_len=256. So, if too large context is given model may not get information about last portions.
  
  ```
  from transformers import T5ForConditionalGeneration, T5Tokenizer
  MODEL_NAME = 'hiiamsid/est5-base-qg'
  model = T5ForConditionalGeneration.from_pretrained(MODEL_NAME)
  tokenizer = T5Tokenizer.from_pretrained(MODEL_NAME)
  model.cuda();
  model.eval();
  def generate_question(text, beams=10, grams=2, num_return_seq=10,max_size=256):
      x = tokenizer(text, return_tensors='pt', padding=True).to(model.device)
      out = model.generate(**x, no_repeat_ngram_size=grams, num_beams=beams, num_return_sequences=num_return_seq, max_length=max_size)
      return tokenizer.decode(out[0], skip_special_tokens=True)
  print(generate_question('Any context in spanish from which question is to be generated'))
  
  ```
  
  ## Citing & Authors
  - Datasets : [squad_es](https://huggingface.co/datasets/squad_es)
  - Model : [hiiamsid/est5-base](hiiamsid/est5-base)