| --- |
| tags: |
| - pyterrier |
| - pyterrier-artifact |
| - pyterrier-dr |
| task_categories: |
| - text-retrieval |
| viewer: false |
| language: |
| - en |
| pretty_name: Dense index of the BRIGHT Sustainable Living collection for PyTerrier |
| --- |
| |
| # Dense index of the BRIGHT Sustainable Living collection for PyTerrier |
|
|
| ## Description |
|
|
| A dense index of the sustainable-living subset of the BRIGHT dataset build with PyTerrier's DR plugin. |
|
|
| ## Usage |
|
|
| You will need to install PyTerrier, and its DR engine: |
|
|
| ```python |
| %pip install pyterrier |
| %pip install pyterrier-dr |
| ``` |
|
|
| ```python |
| # Load the artifact |
| import pyterrier as pt |
| artifact = pt.Artifact.from_hf('pyterrier-tutorial/bright.sustainable.mini.dense') |
| # TODO: Show how you use the artifact |
| ``` |
|
|
| ## Reproduction |
|
|
| ```python |
| import pyterrier as pt |
| from pyterrier_dr import SBertBiEncoder, FlexIndex |
| |
| dataset = pt.get_dataset('irds:bright/sustainable-living') |
| |
| model_mini = SBertBiEncoder( |
| "sentence-transformers/all-MiniLM-L6-v2", |
| batch_size=32, |
| text_field="text" |
| ) |
| |
| dense_path_mini = "./bright-mini.flex" |
| |
| if os.path.exists(dense_path_mini): |
| shutil.rmtree(dense_path_mini) |
| |
| dense_index_mini = FlexIndex(dense_path_mini) |
| dense_indexer_mini = model_mini.doc_encoder() >> dense_index_mini.indexer(mode="overwrite") |
| dense_indexer_mini.index(dataset.get_corpus_iter()) |
| ``` |
|
|
| ## Metadata |
|
|
| ``` |
| { |
| "type": "dense_index", |
| "format": "flex", |
| "vec_size": 384, |
| "doc_count": 60792 |
| } |
| ``` |