Update README.md

README.md

@@ -9,27 +9,11 @@ metrics:
 tags:
 - image-classification
 ---
+# LeNNon Smile Detector (Teeny-Tiny Castle)
 
-# LeNNon-Smile-Detector
+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. 
 
-## Model Overview
-
-The LeNNon-Smile-Detector is a convolutional neural network trained to detect the presence of a human smile in a facial image.
-
-### Details
-
-- **Size:** 2,566,506 parameters
-- **Model type:** Convolutional neural network
-- **Optimizer**: `torch.optim.Adam` with a learning rate of 0.001
-- **Number of Epochs:** 20
-- **Batch Size:** 256
-- **Hardware:** Tesla V4
-- **Emissions:** Not measured
-- **Total Energy Consumption:** Not measured
-
-### How to Use
-
-To run inference on this model, you can use the following code snippet:
+## How to Use
 
 ```python
 import torch
@@ -40,17 +24,17 @@ from huggingface_hub import hf_hub_download
 
 # Download the pytorch model
 hf_hub_download(repo_id="AiresPucrs/LeNNon-Smile-Detector",
-                filename="LeNNon-Smile-Detector.pt",
-                local_dir="./",
-                repo_type="model"
-                )
+ filename="LeNNon-Smile-Detector.pt",
+ local_dir="./",
+ repo_type="model"
+ )
 
 # Download the source implementation of the model's architecture
 hf_hub_download(repo_id="AiresPucrs/LeNNon-Smile-Detector",
-                filename="lennon.py",
-                local_dir="./",
-                repo_type="model"
-                )
+ filename="lennon.py",
+ local_dir="./",
+ repo_type="model"
+ )
 
 # Check if GPU is available
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -62,8 +46,8 @@ model.eval()
 
 # This `transform` object will transform our test images into proper tensors
 transform = transforms.Compose([
-    transforms.Resize((100, 100)),  # Resize the image to 100x100
-    transforms.ToTensor(),
+ transforms.Resize((100, 100)),  # Resize the image to 100x100
+ transforms.ToTensor(),
 ])
 
 image_path = "your_image_path_here"
@@ -76,56 +60,10 @@ tensor = tensor.to(device)
 # forward pass trough the model
 with torch.no_grad():
 
-  outputs = model(tensor)
+ outputs = model(tensor)
 
 # Get the class prediction
 _, predicted = torch.max(outputs.data, 1)
 
 print("Smiling" if predicted.item() > 0 else "Not Smiling")
 ```
-
-## Intended Use
-
-This model was created for research purposes only. Specifically, it was designed to explore discriminatory biases present in a subset of the CelebA dataset (the [CelebA-Smiles](https://huggingface.co/datasets/AiresPucrs/CelebA-Smiles)). We do not recommend any application of this model outside this scope.
-
-
-## Performance Metrics
-
-The model achieved an accuracy of 97% in a test set split containing 5000 images from the [CelebA-Smiles](https://huggingface.co/datasets/AiresPucrs/CelebA-Smiles).
-
-## Training Data
-
-The model was trained on a subset of the [CelebA dataset](https://www.kaggle.com/datasets/jessicali9530/celeba-dataset), i.e., CelebA-Smiles.
-
-CelebA-Smiles contains 50K images. 25K of smiling faces, and 25K of non smiling faces.
-
-Images on the CelebA-Smiles were resized to 100 x 100 pixels before training the model. For more details on the features contained in the CelebA-Smiles dataset, check its [dataset card](https://huggingface.co/datasets/AiresPucrs/CelebA-Smiles).
-
-## Limitations
-
-We performed a simple fairness analysis of our model regarding the sensitive attribute **age**.
-
-According to our analysis, the model has no discriminatory bias regarding this feature. Results can be found [here](https://github.com/Nkluge-correa/teeny-tiny_castle/blob/master/ML%20Fairness/fair_metrics_celeba.ipynb).
-
-Other possible biases were not investigated, but further investigations are likely given that other sensitive attributes present in the training dataset are available.
-
-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
-
-This model is licensed under the Apache License, Version 2.0. See the [LICENSE](LICENSE) file for more details.
-