From 0f94151dc7809128b40ab68ba164742fe1c5b4e6 Mon Sep 17 00:00:00 2001 From: Manuel Romero Date: Fri, 21 Aug 2020 20:18:15 +0200 Subject: [PATCH] Add model card for electricidad-base-generator (#6650) I works like a charm! Look at the output of the example code! --- .../electricidad-base-generator/README.md | 48 +++++++++++++++++++ 1 file changed, 48 insertions(+) create mode 100644 model_cards/mrm8488/electricidad-base-generator/README.md diff --git a/model_cards/mrm8488/electricidad-base-generator/README.md b/model_cards/mrm8488/electricidad-base-generator/README.md new file mode 100644 index 0000000000..b0fc03f8a2 --- /dev/null +++ b/model_cards/mrm8488/electricidad-base-generator/README.md @@ -0,0 +1,48 @@ +--- +language: es +thumbnail: https://i.imgur.com/uxAvBfh.png + + +--- + +## 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 ♥ in Spain