change readme and change weight model

README.md

@@ -1,49 +1,13 @@
-# Conditional GAN Shoe, Sandal, Boot
-=====================================
-
-## Project Overview
----------------
-
-This project implements a Conditional Generative Adversarial Network (CGAN) using the Conditional WGAN-GP architecture to generate images of shoes, sandals, and boots.
-
-### Key Features
-------------
-
-* **Conditional WGAN-GP architecture**: for generating images of shoes, sandals, and boots
-* **Trained on a limited dataset**: due to VRAM constraints
-* **Model architecture and hyperparameters optimized**: for Kaggle environment with 15GB VRAM
-* **Embedding used instead of one-hot encoding**: for training labels to avoid using 0 on labels
-* **Implemented using PyTorch Lightning framework**
-
-## Training Details
----------------
-
-### Training Epochs
-----------------
-
-* Approximately 1000 epochs
-
-### Model Architecture Compromises
------------------------------
-
-* **Reduced Size of latent space (z dim) and Embedding**: due to VRAM limitations
-* **Limited features for generator and critic networks**: due to VRAM limitations
-* **Image size limitations**: due to VRAM limitations
-* **Dataset used**: [Shoe vs Sandal vs Boot Image Dataset (15K Images)](https://www.kaggle.com/datasets/hasibalmuzdadid/shoe-vs-sandal-vs-boot-dataset-15k-images)
-
-## Results
----------
-
-Despite the architectural compromises, the model produces reasonable results. However, the quality of the generated images may not be optimal due to the limited dataset and VRAM constraints.
-
-## Demo
--------------
-The demo of this project is deployed on Hugging Face's model hub and uses the Gradio framework to provide a user-friendly interface for interacting with the model. You can try out the demo by visiting [this link](https://huggingface.co/spaces/SkylarWhite/57894).
-
-
-## Future Work
--------------
-
-* **Experiment with larger datasets and more complex model architectures**
-* **Investigate alternative optimization techniques to improve model performance**
-* **Explore other applications of Conditional GANs in computer vision**
+---
+title: '57894'
+emoji: 🐠
+colorFrom: indigo
+colorTo: purple
+sdk: gradio
+sdk_version: 4.41.0
+app_file: app.py
+pinned: false
+license: mit
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

weights/{epoch=999-step=96000.ckpt → epoch=957-step=1164300.ckpt}

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