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README.md

@@ -1,29 +1,25 @@
 ---
-dataset_info:
-  features:
-  - name: prompt
-    dtype: string
-  - name: completion
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 181611007
-    num_examples: 116722
-  - name: validation
-    num_bytes: 10037679
-    num_examples: 6447
-  - name: test
-    num_bytes: 10217787
-    num_examples: 6553
-  download_size: 122702998
-  dataset_size: 201866473
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: validation
-    path: data/validation-*
-  - split: test
-    path: data/test-*
+tags:
+- trl
 ---
+
+# TL;DR Dataset
+
+## Summary
+
+The TL;DR dataset is a processed version of Reddit posts, specifically curated to train models using the [TRL library](https://github.com/huggingface/trl) for summarization tasks. It leverages the common practice on Reddit where users append "TL;DR" (Too Long; Didn't Read) summaries to lengthy posts, providing a rich source of paired text data for training summarization models.
+
+## Data Structure
+
+- **Format**: [Standard](https://huggingface.co/docs/trl/main/dataset_formats#standard)
+- **Type**: [Prompt-completion](https://huggingface.co/docs/trl/main/dataset_formats#prompt-completion)
+
+Columns:
+- `"pompt"`: The unabridged Reddit post.
+- `"completion"`: The concise "TL;DR" summary appended by the author.
+
+This structure enables models to learn the relationship between detailed content and its abbreviated form, enhancing their summarization capabilities.
+
+## Generation script
+
+The script used to generate this dataset can be found [here](https://github.com/huggingface/trl/blob/main/examples/datasets/tldr.py).