readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: it5-small-dante
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # it5-small-dante
  
  This model is a version of [gsarti/it5-small](https://huggingface.co/gsarti/it5-small) fine-tuned on a dataset called [ita2dante](https://github.com/leobertolazzi/danteIT5). The Dataset dataset contains all the sentences from Dante's [Divine Comedy](https://en.wikipedia.org/wiki/Divine_Comedy) along with paraphrases in contemporary italian (approximately 6k pairs in total) and is scraped from [divinacommedia.weebly.com](divinacommedia.weebly.com).
  
  The fine-tuning task is text style tansfer from modern italian to dantean italian.
  
  
  ## Using the model
  
  ```
  from transformers import AutoTokenzier, AutoModelForSeq2SeqLM
  
  tokenizer = AutoTokenizer.from_pretrained("leobertolazzi/it5-small-dante")
  model = AutoModelForSeq2SeqLM.from_pretrained("leobertolazzi/it5-small-dante")
  ```
  
  Flax and Tensorflow versions of the model are also available:
  ```
  from transformers import FlaxT5ForConditionalGeneration, TFT5ForConditionalGeneration
  
  model_flax = FlaxT5ForConditionalGeneration.from_pretrained("leobertolazzi/it5-small-dante")
  model_tf = TFT5ForConditionalGeneration.from_pretrained("leobertolazzi/it5-small-dante")
  
  ```
  
  ## Training procedure
  
  The code used for the fine-tuning is available in this [repo](https://github.com/leobertolazzi/danteIT5)
  
  ## Intended uses & limitations
  
  The biggest limitation for this project is the size of the ita2dante dataset. In fact, it consists only of 6K sentences whereas [gsarti/it5-small](https://huggingface.co/gsarti/it5-small) has more than 70M parameters.
  
  For this reason the results can be far from perfect, but some nice style translations can also be obtained.
  
  It would be nice to expand ita2dante with text and paraphrases from other medieval italian poets!
  
  ### Framework versions
  
  - Transformers 4.26.0
  - TensorFlow 2.9.2
  - Tokenizers 0.13.2
  