Update README info

README.md

@@ -1,3 +1,52 @@
 ---
 license: apache-2.0
+language:
+- es
+datasets:
+- large_spanish_corpus
+- bertin-project/mc4-es-sampled
+- oscar-corpus/OSCAR-2109
 ---
+
+# BARTO (base-sized model) 
+
+BARTO model pre-trained on Spanish language. It was introduced in the paper [Sequence-to-Sequence Spanish Pre-trained Language Models](https://arxiv.org/abs/2309.11259). 
+
+## Model description
+
+BARTO is a BART-based model (transformer encoder-decoder) with a bidirectional (BERT-like) encoder and an autoregressive (GPT-like) decoder. BART is pre-trained by (1) corrupting text with an arbitrary noising function and (2) learning a model to reconstruct the original text.
+
+BARTO is particularly effective when fine-tuned for text generation (e.g. summarization, translation) but also works well for comprehension tasks (e.g. text classification, question answering).
+
+## Intended uses
+
+You can use the raw model for text infilling. However, the model is mainly meant to be fine-tuned on a supervised dataset.
+
+### How to use
+
+Here is how to use this model in PyTorch:
+
+```python
+from transformers import AutoTokenizer, AutoModel
+
+tokenizer = AutoTokenizer.from_pretrained('vgaraujov/bart-base-spanish')
+model = AutoModel.from_pretrained('vgaraujov/bart-base-spanish')
+
+inputs = tokenizer("Hola amigo, bienvenido a casa.", return_tensors="pt")
+outputs = model(**inputs)
+
+last_hidden_states = outputs.last_hidden_state
+```
+
+### Citation (BibTeX)
+
+```bibtex
+@misc{araujo2023sequencetosequence,
+      title={Sequence-to-Sequence Spanish Pre-trained Language Models}, 
+      author={Vladimir Araujo and Maria Mihaela Trusca and Rodrigo Tufiño and Marie-Francine Moens},
+      year={2023},
+      eprint={2309.11259},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```