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README.md

@@ -1,27 +1,60 @@
 ---
-dataset_info:
-  features:
-  - name: text
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 5019270
-    num_examples: 1003854
-  - name: validation
-    num_bytes: 278850
-    num_examples: 55770
-  - name: test
-    num_bytes: 278850
-    num_examples: 55770
-  download_size: 924470
-  dataset_size: 5576970
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: validation
-    path: data/validation-*
-  - split: test
-    path: data/test-*
+language:
+- en
+license: cc0-1.0
+task_categories:
+- text-generation
+pretty_name: Shakespeare Complete Works - Dialogue Format
+tags:
+- shakespeare
+- dialogue
+- drama
+- literature
 ---
+
+Taken from Andrej Karpathy and repurposed for UofT's CSC 413 Deep Learning 
+40,000 lines of Shakespeare from a variety of Shakespeare's plays. Featured in Andrej Karpathy's blog post 'The Unreasonable Effectiveness of Recurrent Neural Networks': http://karpathy.github.io/2015/05/21/rnn-effectiveness/.
+
+
+
+## Usage
+
+To use for e.g. character modelling:
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("r-three/shakespeare-dialogue-blob")
+
+# Access examples
+for example in dataset['train'][:5]:
+    print(f"{example['character']}: {example['text']}")
+
+# Filter by character
+hamlet_lines = dataset['train'].filter(lambda x: x['character'] == 'Hamlet')
+
+# Get character statistics
+from collections import Counter
+characters = Counter(dataset['train']['character'])
+print(f"Top 10 characters: {characters.most_common(10)}")
+```
+
+## Source
+
+Public domain works by William Shakespeare, sourced from the Karpathy char-rnn repository.
+
+To cite:
+```
+@misc{
+  author={Karpathy, Andrej},
+  title={char-rnn},
+  year={2015},
+  howpublished={\url{https://github.com/karpathy/char-rnn}}
+}
+```
+
+
+## License
+
+This dataset is in the public domain (CC0-1.0) as Shakespeare's works are no longer under copyright.