Update README.md

README.md

@@ -13,8 +13,8 @@ tags:
 MIRNet-based low-light image enhancer specialized on restoring dark images from events (concerts, parties, clubs...).
 
 ## Project source-code and further documentation
-Documentation about pre-training, fine-tuning, model architecture, usage and all source code used for building and inference can be found in the [GitHub repository of the project](https://github.com/dblasko/low-light-event-img-enhancer/).
-This currently stores the PyTorch model weights and model definition, a HuggingFace pipeline will be implemented in the future. 
+Documentation about pre-training, fine-tuning, model architecture, usage and all source code used for building and inference can be found in the [GitHub repository of the project](https://github.com/dblasko/low-light-event-img-enhancer/).  
+This page currently stores the PyTorch model weights and model definition, a HuggingFace pipeline will be implemented in the future. 
 
 ## Using the model
 To use the model, you need to have the `model` folder, that you can dowload from this repository as well as on [GitHub](https://github.com/dblasko/low-light-event-img-enhancer/), present in your project folder.
@@ -24,7 +24,7 @@ Then, the following code can be used to download the model weights from HuggingF
 import torch
 import torchvision.transforms as T
 from PIL import Image
-from huggingface_hub import hf_hub_url, cached_download
+from huggingface_hub import hf_hub_download
 from model.MIRNet.model import MIRNet
 
 device = (