Upload folder using huggingface_hub

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2023 Hussam Alafandi
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -0,0 +1,39 @@
+# AutoEncoder
+
+A simple autoencoder trained on MNIST.
+
+This model is part of the "Introduction to Generative AI" course.  
+For more details, visit the [GitHub repository](https://github.com/hussamalafandi/Generative_AI).
+
+## Model Description
+
+The AutoEncoder is a neural network designed to compress and reconstruct input data. It consists of an encoder that compresses the input into a latent space and a decoder that reconstructs the input from the latent representation.
+
+## Training Details
+
+- **Dataset**: MNIST (handwritten digits)
+- **Loss Function**: Mean Squared Error (MSE)
+- **Optimizer**: Adam
+- **Learning Rate**: 0.001
+- **Epochs**: 40
+- **Latent dim**: 10
+
+## Tracking
+
+For detailed training logs and metrics, visit the [Weights & Biases run](https://wandb.ai/hussam-alafandi/mnist-autoencoder/runs/f81c7dgf?nw=nwuserhussamalafandi).
+
+## Load Model
+
+```python
+from model import AutoEncoder
+import torch
+
+model = AutoEncoder()
+model.load_state_dict(torch.load("model.pth"))
+model.eval()
+```
+
+
+## License
+
+This project is licensed under the MIT License. See the LICENSE file for details.

autoencoder_mnist.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ead8b660eb1ca145b7e1385919a501e36505238f111574d7d9c696ef8bf672bd
+size 882898