Update README.md

README.md

@@ -25,11 +25,8 @@ Transform grayscale landscape images into vibrant, full-color visuals with this
 
 ## Notebook
 Explore the implementation in our Jupyter notebook:  
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/danhtran2mind/autoencoder-grayscale2color-landscape-from-scratch/blob/main/notebooks/autoencoder-grayscale-to-color-landscape.ipynb)
-[![Open in SageMaker](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/danhtran2mind/autoencoder-grayscale2color-landscape-from-scratch/blob/main/notebooks/autoencoder-grayscale-to-color-landscape.ipynb)
-[![Open in Deepnote](https://deepnote.com/buttons/launch-in-deepnote-small.svg)](https://deepnote.com/launch?url=https://github.com/danhtran2mind/autoencoder-grayscale2color-landscape-from-scratch/blob/main/notebooks/autoencoder-grayscale-to-color-landscape.ipynb)
-[![JupyterLab](https://img.shields.io/badge/Launch-JupyterLab-orange?logo=Jupyter)](https://mybinder.org/v2/gh/danhtran2mind/autoencoder-grayscale2color-landscape-from-scratch/main?filepath=autoencoder-grayscale-to-color-landscape.ipynb)
-[![View on GitHub](https://img.shields.io/badge/View%20on-GitHub-181717?logo=github)](https://github.com/danhtran2mind/autoencoder-grayscale2color-landscape-from-scratch/blob/main/notebooks/autoencoder-grayscale-to-color-landscape.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#fileId=https://huggingface.co/danhtran2mind/autoencoder-grayscale2color-landscape/blob/main/notebooks/autoencoder-grayscale-to-color-landscape.ipynb)
+[![View on HuggingFace](https://img.shields.io/badge/View%20on-HuggingFace-181717?logo=huggingface)](https://huggingface.co/danhtran2mind/autoencoder-grayscale2color-landscape/blob/main/notebooks/autoencoder-grayscale-to-color-landscape.ipynb)
 
 ## Dataset
 Details about the dataset are available in the [README Dataset](./dataset/README.md). 📂
@@ -48,8 +45,9 @@ Experience the brilliance of our cutting-edge technology! Transform grayscale la
 
 ### Step 1: Clone the Repository
 ```bash
-git clone https://github.com/danhtran2mind/autoencoder-grayscale2color-landscape-from-scratch
-cd /autoencoder-grayscale2color-landscape-from-scratch
+git clone https://huggingface.co/danhtran2mind/autoencoder-grayscale2color-landscape
+cd ./autoencoder-grayscale2color-landscape
+git lfs pull
 ```
 
 ### Step 2: Install Dependencies
@@ -82,16 +80,6 @@ Download and load the autoencoder model from a remote source if it’s not alrea
 load_model_path = "./ckpts/best_model.h5"
 os.makedirs(os.path.dirname(load_model_path), exist_ok=True)
 
-if not os.path.exists(load_model_path):
-    url = "https://huggingface.co/danhtran2mind/autoencoder-grayscale2color-landscape/resolve/main/ckpts/best_model.h5"
-    print(f"Downloading model from {url}...")
-    with requests.get(url, stream=True) as response:
-        response.raise_for_status()
-        with open(load_model_path, "wb") as f:
-            for chunk in response.iter_content(chunk_size=8192):
-                f.write(chunk)
-    print("Model downloaded successfully.")
-
 print(f"Loading model from {load_model_path}...")
 loaded_autoencoder = tf.keras.models.load_model(
     load_model_path, custom_objects={"SpatialAttention": SpatialAttention}
@@ -185,7 +173,7 @@ The output will be a side-by-side comparison of the input grayscale image and th
 - **Early Stopping**: Monitors `val_loss`, patience of 20 epochs, restores best weights.
 - **ReduceLROnPlateau**: Monitors `val_loss`, reduces learning rate by 50% after 5 epochs, minimum learning rate of 1e-6.
 - **BackupAndRestore**: Saves checkpoints to `./ckpts/backup`.
-- 
+
 ## Metrics
 - **PSNR (Validation)**: 21.70 📈
 
@@ -202,4 +190,4 @@ The output will be a side-by-side comparison of the input grayscale image and th
     ```
 
 ## Contact
-For questions or issues, reach out via the [GitHub Issues](https://github.com/danhtran2mind/autoencoder-grayscale2color-landscape-from-scratch/issues) tab. 🚀
+For questions or issues, reach out via the [HuggingFace Community](https://huggingface.co/danhtran2mind/autoencoder-grayscale2color-landscape/discussions) tab. 🚀