Update README.md

README.md

@@ -40,7 +40,47 @@ This dataset contains hallucinated cyclic peptide scaffold structures (in CIF fo
 - **Repository:** https://zenodo.org/records/15164650
 - **Paper [optional]:** Rettie, S.A., Campbell, K.V., Bera, A.K. et al. Cyclic peptide structure prediction and design using AlphaFold2. *Nature Communications* **16**, 4730 (2025). https://doi.org/10.1038/s41467-025-59940-7
 
-## Uses
+## Quickstart Usage
+### Install HuggingFace Datasets package
+Each subset can be loaded into python using the Huggingface [datasets](https://huggingface.co/docs/datasets/index) library.
+First, from the command line install the `datasets` library
+
+    $ pip install datasets
+
+then, from within python load the datasets library
+
+    >>> import datasets
+
+
+### Load dataset   
+Load the 'RosettaCommons/AfCycDesign' datasets.
+
+    >>> AfCycDesign = datasets.load_dataset('RosettaCommons/AfCycDesign')
+    Downloading readme: 9.67kB [00:00, 3.57MB/s]
+    Downloading data: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 2.94M/2.94M [00:00<00:00, 6.99MB/s]
+    Downloading data: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████| 544/544 [00:00<00:00, 4.22kB/s]
+    Generating afcycpep_hallucinated split: 100%|███████████████████████████████████████████████████████████████| 20656/20656 [00:00<00:00, 246500.54 examples/s]
+    Generating afcycpep_experimental split: 100%|█████████████████████████████████████████████████████████████████████████| 8/8 [00:00<00:00, 3582.58 examples/s]
+
+and the dataset is loaded as a datasets.arrow_dataset.Dataset
+
+    >>> AfCycDesign
+    DatasetDict({
+        afcycpep_hallucinated: Dataset({
+            features: ['ID', 'sequence', 'nmer', 'rosetta_score', 'hf_path', 'Type'],
+            num_rows: 20656
+        })
+        afcycpep_experimental: Dataset({
+            features: ['ID', 'sequence', 'nmer', 'rosetta_score', 'hf_path', 'Type'],
+            num_rows: 8
+        })
+    })
+
+which is a column oriented format that can be accessed directly, converted in to a pandas.DataFrame, or parquet format, e.g.
+
+    >>> AfCycDesign.data.column('sequence')
+    >>> AfCycDesign.to_pandas()
+    >>> AfCycDesign.to_parquet("dataset.parquet")    
 
 ### Direct Use