Create README.md

README.md

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+---
+pretty_name: MS MARCO Passage Augmented
+language:
+  - en
+license: unknown
+task_categories:
+  - retrieval
+  - text-retrieval
+task_ids:
+  - document-retrieval
+  - passage-retrieval
+size_categories:
+  - 1M<n<10M
+
+dataset_info:
+  features:
+    - name: query_id
+      dtype: string
+
+    - name: query
+      dtype: string
+
+    - name: positive_passages
+      sequence:
+        - name: docid
+          dtype: string
+        - name: title
+          dtype: string
+        - name: text
+          dtype: string
+
+    - name: negative_passages
+      sequence:
+        - name: docid
+          dtype: string
+        - name: title
+          dtype: string
+        - name: text
+          dtype: string
+
+  splits:
+    - name: train
+      num_bytes: null
+      num_examples: null
+
+    - name: dev
+      num_bytes: null
+      num_examples: null
+
+    - name: dl19
+      num_bytes: null
+      num_examples: null
+
+    - name: dl20
+      num_bytes: null
+      num_examples: null
+
+  download_size: null
+  dataset_size: null
+
+citation: |
+  @misc{bajaj2018ms,
+    title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
+    author={Payal Bajaj and Daniel Campos and Nick Craswell and Li Deng and Jianfeng Gao and Xiaodong Liu
+    and Rangan Majumder and Andrew McNamara and Bhaskar Mitra and Tri Nguyen and Mir Rosenberg and Xia Song
+    and Alina Stoica and Saurabh Tiwary and Tong Wang},
+    year={2018},
+    eprint={1611.09268},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+  }
+
+---
+
+# MS MARCO Passage Augmented
+
+MS MARCO passage retrieval dataset with positive and negative passages.
+
+## Features
+
+- `query_id`: query identifier
+- `query`: search query
+- `positive_passages`: relevant passages
+- `negative_passages`: non-relevant passages