pytorch electra masked-lm es transformers fill-mask
.gitattributes README.md config.json pytorch_model.bin vocab.txt
---
language: es
thumbnail: https://i.imgur.com/uxAvBfh.png
widget:
- text: "Madrid es una ciudad muy [MASK] en España."


---

## ELECTRICIDAD: The Spanish Electra [Imgur](https://imgur.com/uxAvBfh)

**Electricidad-base-generator** (uncased) is a ```base``` Electra like model (generator in this case) trained on a + 20 GB of  the [OSCAR](https://oscar-corpus.com/) Spanish corpus.

As mentioned in the original [paper](https://openreview.net/pdf?id=r1xMH1BtvB):
**ELECTRA** is a new method for self-supervised language representation learning. It can be used to pre-train transformer networks using relatively little compute. ELECTRA models are trained to distinguish "real" input tokens vs "fake" input tokens generated by another neural network, similar to the discriminator of a [GAN](https://arxiv.org/pdf/1406.2661.pdf). At small scale, ELECTRA achieves strong results even when trained on a single GPU. At large scale, ELECTRA achieves state-of-the-art results on the [SQuAD 2.0](https://rajpurkar.github.io/SQuAD-explorer/) dataset.

For a detailed description and experimental results, please refer the paper [ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators](https://openreview.net/pdf?id=r1xMH1BtvB).





## Fast example of usage 🚀

```python
from transformers import pipeline

fill_mask = pipeline(
    "fill-mask",
    model="mrm8488/electricidad-base-generator",
    tokenizer="mrm8488/electricidad-base-generator"
)

print(
    fill_mask(f"HuggingFace está creando {fill_mask.tokenizer.mask_token} que la comunidad usa para resolver tareas de NLP.")
)

# Output: [{'sequence': '[CLS] huggingface esta creando herramientas que la comunidad usa para resolver tareas de nlp. [SEP]', 'score': 0.0896105170249939, 'token': 8760, 'token_str': 'herramientas'}, ...]

```

## Acknowledgments

I thank [🤗/transformers team](https://github.com/huggingface/transformers) for allowing me to train the model (specially to [Julien Chaumond](https://twitter.com/julien_c)).



> Created by [Manuel Romero/@mrm8488](https://twitter.com/mrm8488)

> Made with <span style="color: #e25555;">&hearts;</span> in Spain
