Add dataset documentation

README.md

@@ -38,11 +38,9 @@ Original data source: https://zenodo.org/records/8196385/files/HDFS_v1.zip?downl
 
 ## Preprocessing
 
-The logs have been preprocessed to:
-1. Extract structured fields (timestamp, component, etc.)
-2. Identify and standardize event types
-3. Remove block IDs from parameter lists to prevent data leakage
-4. Add special tokens for event type separation
+We preprocess the logs using the Drain algorithm to extract structured fields and identify event types.
+We then encode the logs using a pretrained tokenizer and add special tokens to separate event types. This
+dataset should be immediately usable for training and testing models for log-based anomaly detection.
 
 ## Intended Uses
 
@@ -51,6 +49,8 @@ This dataset is designed for:
 - Evaluating log sequence prediction models
 - Benchmarking different approaches to log-based anomaly detection
 
+see [honicky/pythia-14m-hdfs-logs](https://huggingface.co/honicky/pythia-14m-hdfs-logs) for an example model.
+
 ## Citation
 
 If you use this dataset, please cite the original HDFS paper: