MS MARCO is a large scale information retrieval corpus that was created based on real user search queries using Bing search engine. The provided models can be used for semantic search, i.e., given keywords / a search phrase / a question, the model will find passages that are relevant for the search query.
The training data constist of over 500k examples, while the complete  corpus consist of over 8.8 Million passages.
Usage with SentenceTransformers
Pre-trained models can be used like this:
python
from sentence_transformers import CrossEncoder
model = CrossEncoder('model_name', max_length=512)
scores = model.predict([('Query', 'Paragraph1'), ('Query', 'Paragraph2') , ('Query', 'Paragraph3')])
Usage with Transformers
```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
