Update README.md

README.md

@@ -60,17 +60,52 @@ COCO is a large-scale object detection, segmentation, and captioning dataset. CO
 Disclaimer: The team releasing COCO did not upload the dataset to the Hub and did not write a dataset card. 
 These steps were done by the Hugging Face team.
 
-### Supported Tasks and Leaderboards
+### Supported Tasks
 
-[More Information Needed](https://cocodataset.org/#home)
+- [Sentence Transformers](https://huggingface.co/sentence-transformers) training; useful for semantic search and sentence similarity. 
 
 ### Languages
 
-[More Information Needed](https://cocodataset.org/#home)
+- English.
 
 ## Dataset Structure
 
-[More Information Needed](https://cocodataset.org/#format-data)
+Each example in the dataset contains quintets of similar sentences and is formatted as a dictionary with the key "set" and a list with the sentences as "value":
+
+```
+{"set": [sentence_1, sentence_2, sentence3, sentence4, sentence5]}
+{"set": [sentence_1, sentence_2, sentence3, sentence4, sentence5]}
+...
+{"set": [sentence_1, sentence_2, sentence3, sentence4, sentence5]}
+```
+
+This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar pairs of sentences.
+
+### Usage Example
+
+Install the 🤗 Datasets library with `pip install datasets` and load the dataset from the Hub with:
+
+```python
+from datasets import load_dataset
+dataset = load_dataset("embedding-data/coco_captions")
+```
+The dataset is loaded as a `DatasetDict` and has the format:
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['set'],
+        num_rows: 82783
+    })
+})
+```
+
+Review an example `i` with:
+
+```python
+dataset["train"][i]["set"]
+```
+
 
 ### Data Instances