Update README.md

README.md

@@ -7,29 +7,13 @@ language:
 - en
 - pt
 ---
-# GRU-eng-por
+# GRU EN-PT (Teeny-Tiny Castle)
 
-## Model Overview
+This model is part of a tutorial tied to the [Teeny-Tiny Castle](https://github.com/Nkluge-correa/TeenyTinyCastle), an open-source repository containing educational tools for AI Ethics and Safety research. 
 
-The GRU-eng-por model is a Recurrent Neural Network (RNN) for machine translation tasks (English-Portuguese).
-
-### Details
-
-- **Size:** 42,554,912  parameters
-- **Model type:** Recurrent neural network
-- **Optimizer**: `rmsprop`
-- **Number of Epochs:** 15
-- **Dimensionality of the embedding layer** = 256
-- **dimensionality of the feed-forward network** = 1024
-- **Hardware:** Tesla T4
-- **Emissions:** Not measured
-- **Total Energy Consumption:** Not measured
-
-### How to Use
+## How to Use
 
 ```python
-!pip install huggingface_hub["tensorflow"] -q
-
 from huggingface_hub import from_pretrained_keras
 from huggingface_hub import hf_hub_download
 import tensorflow as tf
@@ -122,84 +106,6 @@ for sentence in eng_sentences:
     print(f"English sentence:\n{sentence}")
     print(f'Portuguese translation:\n{decode_sequence(sentence)}')
     print('-' * 50)
-```
-
-This will output the following:
-```
-English sentence:
-What is its name?
-Portuguese translation:
-[start] qual é o nome [end]
---------------------------------------------------
-English sentence:
-How old are you?
-Portuguese translation:
-[start] quantos anos você tem [end]
---------------------------------------------------
-English sentence:
-I know you know where Mary is.
-Portuguese translation:
-[start] eu sei que você sabe onde maria está [end]
---------------------------------------------------
-English sentence:
-We will show Tom.
-Portuguese translation:
-[start] nós vamos tom [end]
---------------------------------------------------
-English sentence:
-What do you all do?
-Portuguese translation:
-[start] o que vocês faz [end]
---------------------------------------------------
-English sentence:
-Don't do it!
-Portuguese translation:
-[start] não faça isso [end]
---------------------------------------------------
-```
-## Intended Use
-
-This model was created for research purposes only. Specifically, it was designed to translate sentences from English to Portuguese. 
-We do not recommend any application of this model outside this scope.
-
-## Performance Metrics
 
-Accuracy is a crude way to monitor validation-set performance during this task. 
-On average, this model correctly predicts words in the Portuguese sentence: 65%.
-However, next-token accuracy isn't an excellent metric for machine translation models. 
-During inference, you're generating the target sentence from scratch and can't rely on previously generated tokens (a.k.a. 100% correctness does not mean you have a good translator). 
-We would likely use "_BLEU scores_" in real-world machine translation applications to evaluate our models.
 
-## Training Data
-
- [English-portuguese translation](https://www.kaggle.com/datasets/nageshsingh/englishportuguese-translation).
-
- The dataset consists of a set of English and Portuguese sentences.
-
-
-## Limitations
-
-Translations are far from perfect. To improve this model, we could:
-
-1. Use a deep stack of recurrent layers for both the encoder and the decoder.
-2. Or, we could use an `LSTM` instead of a `GRU`.
-
-In conclusion, we do not recommend using this model in real-world applications. 
-It was solely developed for academic and educational purposes.
-
-## Cite as 🤗
-
-```latex
-@misc{teenytinycastle,
-    doi = {10.5281/zenodo.7112065},
-    url = {https://github.com/Nkluge-correa/teeny-tiny_castle},
-    author = {Nicholas Kluge Corr{\^e}a},
-    title = {Teeny-Tiny Castle},
-    year = {2024},
-    publisher = {GitHub},
-    journal = {GitHub repository},
-}
 ```
-
-## License
-The GRU-eng-por is licensed under the Apache License, Version 2.0. See the LICENSE file for more details.