Update README.md

README.md

@@ -67,33 +67,29 @@ model-index:
 
 ## Model Overview
 
-This repository contains **BiLSTM** models for **fake news detection in Portuguese**.
-Models are trained and evaluated on corpora derived from Brazilian Portuguese dataset **[Fake.br](https://github.com/roneysco/Fake.br-Corpus)**.
+This repository contains a trained **BiLSTM** model for **fake news detection in Portuguese**.
+The model was trained and evaluated on corpora derived from Brazilian Portuguese dataset **[Fake.br](https://github.com/roneysco/Fake.br-Corpus)**.
 
 - **Architecture**: Bidirectional LSTM (Keras)
 - **Task**: Binary text classification (Fake vs. True)
 - **Language**: Portuguese (`pt`)
 - **Framework**: Keras / TensorFlow
+- **Training source code**: https://github.com/viniciuszani/portuguese-fake-new-classifiers
 
 ---
 
 ## Available Variants
 
-- **bilstm-combined**
-  Fine-tuned on the aligned combined corpus (`data/corpus_*` at project root).
+- [**bilstm-combined**](https://huggingface.co/vzani/portuguese-fake-news-classifier-bilstm-combined)
+  Fine-tuned using the [combined dataset](https://huggingface.co/datasets/vzani/corpus-combined) from Fake.br and FakeTrue.Br.
 
-- **bilstm-fake-br**
-  Fine-tuned on **Fake.br**.
-  The corresponding corpus is available in `corpus/` (including preprocessed and size-normalized texts when applicable).
+- [**bilstm-fake-br**](https://huggingface.co/vzani/portuguese-fake-news-classifier-bilstm-fake-br)
+  Fine-tuned using the [Fake.br dataset](https://huggingface.co/datasets/vzani/corpus-fake-br) from Fake.br.
 
-- **bilstm-faketrue-br**
-  Fine-tuned on **FakeTrue.Br**.
-  Includes aligned splits and the original CSV when available.
+- [**bilstm-faketrue-br**](https://huggingface.co/vzani/portuguese-fake-news-classifier-bilstm-faketrue-br)
+  Fine-tuned using the [FakeTrue.Br dataset](https://huggingface.co/datasets/vzani/corpus-faketrue-br) from FakeTrue.Br.
 
-Each variant ships with:
-- `confusion_matrix.png`
-- `final_classification_report.parquet`
-- `final_predictions.parquet`
+Each variant has its own confusion matrix, classification report, and predictions stored as artifacts.
 
 ---
 
@@ -127,16 +123,6 @@ These files provide per-class performance and prediction logs for reproducibilit
 
 ---
 
-## Corpus
-
-The corpora used for training and evaluation are provided in the `corpus/` folder.
-
-- **Combined (root folder)**: `corpus_train_df.parquet`, `corpus_test_df.parquet`, `corpus_df.parquet`, `corpus_alinhado_df.parquet`.
-- **Fake.br**: `corpus_train_df.parquet`, `corpus_test_df.parquet`, `corpus_df.parquet`, `corpus_alinhado_df.parquet`.
-- **FakeTrue.Br**: `corpus_train_df.parquet`, `corpus_test_df.parquet`, `corpus_df.parquet`, `corpus_alinhado_df.parquet` and `FakeTrueBr_corpus.csv`.
-
----
-
 ## How to Use
 
 This model is a **Keras** model stored as `final_bilstm_model.keras`.
@@ -174,10 +160,30 @@ The expected output is a Tuple where the first entry represents the classificati
 (False, 0.997499808203429)
 ```
 
+## Source code
+
+You can find the source code that produced this model in the repository below:
+- https://github.com/viniciuszani/portuguese-fake-new-classifiers
+
+The source contains all the steps from data collection, evaluation, hyperparameter fine tuning, final model tuning and publishing to HuggingFace.
+If you use it, please remember to credit the author and/or cite the work.
+
 ## License
 
-[Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
+- Base model BERTimbau: [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
+- Fine-tuned models and corpora: Released under the same license for academic and research use.
 
 ## Citation
 
-Coming soon.
+```bibtex
+@misc{zani2025portuguesefakenews,
+  author       = {ZANI, Vinícius Augusto Tagliatti},
+  title        = {Avaliação comparativa de técnicas de processamento de linguagem natural para a detecção de notícias falsas em Português},
+  year         = {2025},
+  pages        = {61},
+  address      = {São Carlos},
+  school       = {Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo},
+  type         = {Trabalho de Conclusão de Curso (MBA em Inteligência Artificial e Big Data)},
+  note         = {Orientador: Prof. Dr. Ivandre Paraboni}
+}
+```