Update README.md

README.md

@@ -22,12 +22,12 @@ inference:
 # Spanish RoBERTa-base trained on BNE finetuned for CAPITEL Named Entity Recognition (NER) dataset.
 RoBERTa-base-bne is a transformer-based masked language model for the Spanish language. It is based on the [RoBERTa](https://arxiv.org/abs/1907.11692) base model and has been pre-trained using the largest Spanish corpus known to date, with a total of 570GB of clean and deduplicated text processed for this work, compiled from the web crawlings performed by the  [National Library of Spain (Biblioteca Nacional de España)](http://www.bne.es/en/Inicio/index.html) from 2009 to 2019.
 
-Original pre-trained model can be found here: https://huggingface.co/BSC-TeMU/roberta-base-bne
+Original pre-trained model can be found here: https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne
 
 ## Dataset
 The dataset used is the one from the [CAPITEL competition at IberLEF 2020](https://sites.google.com/view/capitel2020) (sub-task 1).
 
-**IMPORTANT ABOUT THIS MODEL:** We modified the dataset to make this model more robust to general Spanish input. In the Spanish language all the name entities are capitalized, as this dataset has been elaborated by experts, it is totally correct in terms of Spanish language. We randomly took some entities and we lower-cased some of them for the model to learn not only that the named entities are capitalized, but also the structure of a sentence that should contain a named entity. For instance: "My name is [placeholder]", this [placeholder] should be a named entity even though it is not written capitalized. The model trained on the original capitel dataset can be found here: https://huggingface.co/BSC-TeMU/roberta-base-bne-capitel-ner
+**IMPORTANT ABOUT THIS MODEL:** We modified the dataset to make this model more robust to general Spanish input. In the Spanish language all the name entities are capitalized, as this dataset has been elaborated by experts, it is totally correct in terms of Spanish language. We randomly took some entities and we lower-cased some of them for the model to learn not only that the named entities are capitalized, but also the structure of a sentence that should contain a named entity. For instance: "My name is [placeholder]", this [placeholder] should be a named entity even though it is not written capitalized. The model trained on the original capitel dataset can be found here: https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne-capitel-ner
 
 Examples:
 
@@ -42,7 +42,7 @@ Model trained on original data:
 ## Evaluation and results
 F1 Score: 0.8867
 
-For evaluation details visit our [GitHub repository](https://github.com/PlanTL-SANIDAD/lm-spanish).
+For evaluation details visit our [GitHub repository](https://github.com/PlanTL-GOB-ES/lm-spanish).
 
 
 ## Citing