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---
# pretty_name: "" # Example: "MS MARCO Terrier Index"
tags:
- pyterrier
- pyterrier-artifact
- pyterrier-artifact.dense_index
- pyterrier-artifact.dense_index.flex
task_categories:
- text-retrieval
viewer: false
---
# webis-touche2020.retromae.flex
## Description
RetroMAE index for Webis-Touche (v2)
## Usage
```python
# Load the artifact
import pyterrier_alpha as pta
artifact = pta.Artifact.from_hf('pyterrier/webis-touche2020.retromae.flex')
artifact.np_retriever()
```
## Benchmarks
`webis-touche2020/v2`
| name | nDCG@10 | R@1000 |
|:----------|----------:|---------:|
| np (flat) | 0.3258 | 0.6429 |
## Reproduction
```python
import pyterrier as pt
from tqdm import tqdm
import ir_datasets
from pyterrier_dr import FlexIndex, RetroMAE
pipeline = RetroMAE.msmarco_distill() >> FlexIndex("webis-touche2020/v2.retromae.flex")
dataset = ir_datasets.load('beir/webis-touche2020/v2')
docs = ({'docno': d.doc_id, 'text': '{title}\n{text}'.format(**d._asdict())} for d in tqdm(dataset.docs))
pipeline.index(docs)
```
## Metadata
```
{
"type": "dense_index",
"format": "flex",
"vec_size": 768,
"doc_count": 382545
}
```
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