Update README for loading dataset from caption-free branch

Updated the README file to include instructions on loading the COCO 2017 Colorization Dataset from the caption-free branch of the repository. Added usage examples for loading both the train and validation splits from the caption-free branch. The README now provides clear guidance on how to choose between the main branch for original captions and the caption-free branch for prompts-free captions when loading the dataset.

README.md

@@ -91,10 +91,30 @@ unzip train2017.zip
 unzip val2017.zip
 ```
 
+### Branches
+
+- **main:** Provides the original captions sentences.
+- **caption-free:** Provides captions with random prompts selected from the following list:
+
+```python
+sentences = [
+    "Add colors to this image",
+    "Give realistic colors to this image",
+    "Add realistic colors to this image",
+    "Colorize this grayscale image",
+    "Colorize this image",
+    "Restore the original colors of this image",
+    "Make this image colorful",
+    "Colorize this image as if it was taken with a color camera",
+    "Create the original colors of this image"
+]
+```
+
 ### Loading the Dataset
 
 You can load this dataset using the Hugging Face `datasets` library:
 
+#### Main Branch
 ```python
 from datasets import load_dataset
 
@@ -105,6 +125,19 @@ train_dataset = load_dataset("nickpai/coco2017-colorization", split="train")
 val_dataset = load_dataset("nickpai/coco2017-colorization", split="validation")
 ```
 
+#### Caption-Free Branch
+```python
+from datasets import load_dataset
+
+# Load the train split of the colorization dataset from the caption-free branch
+train_dataset = load_dataset("nickpai/coco2017-colorization", split="train", revision="caption-free")
+
+# Load the validation split of the colorization dataset from the caption-free branch
+val_dataset = load_dataset("nickpai/coco2017-colorization", split="validation", revision="caption-free")
+```
+
+
+
 ## Filtering Criteria
 
 ### 1. Grayscale Images