Update README.md

README.md

@@ -15,6 +15,13 @@ This BERT-based text classifier was developed as a thesis project for the Comput
 The model is designed to detect fake news in Spanish and was fine-tuned on the *dccuchile/bert-base-spanish-wwm-uncased* model using a specific set of hyperparameters. 
 It was trained on a dataset containing 125,000 Spanish news articles collected from various regions, both true and false.
 
+## Team Members
+- **[Azul Fuentes](https://github.com/azu26)**
+- **[Dante Reinaudo](https://github.com/DanteReinaudo)** 
+- **[Lucía Pardo](https://github.com/luciaPardo)**
+- **[Roberto Iskandarani](https://github.com/Robert-Iskandarani)**
+
+
 ## Model Details
 * **Base Mode**: dccuchile/bert-base-spanish-wwm-uncased
 * **Hyperparameters**: 
@@ -50,8 +57,8 @@ pip install transformers torch
 ```python
 from transformers import BertForSequenceClassification, BertTokenizer
 
-model = BertForSequenceClassification.from_pretrained("VerificadoProfesional/SaBERT-Spanish-Fake-News ")
-tokenizer = BertTokenizer.from_pretrained("VerificadoProfesional/SaBERT-Spanish-Fake-News ")
+model = BertForSequenceClassification.from_pretrained("VerificadoProfesional/SaBERT-Spanish-Fake-News")
+tokenizer = BertTokenizer.from_pretrained("VerificadoProfesional/SaBERT-Spanish-Fake-News")
 ```
 
 ### Predict Function