You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
See the [Quickstart](https://webis-de.github.io/lightning-ir/quickstart.html) guide for an introduction to Lightning IR. The [Documentation](https://webis-de.github.io/lightning-ir/) provides a detailed overview of the library's functionality.
31
+
30
32
The easiest way to use Lightning IR is via the CLI. It uses the [PyTorch Lightning CLI](https://lightning.ai/docs/pytorch/stable/cli/lightning_cli.html#lightning-cli) and adds additional options to provide a unified interface for fine-tuning and running neural ranking models.
31
33
32
34
The behavior of the CLI can be customized using yaml configuration files. See the [configs](configs) directory for several example configuration files. For example, the following command can be used to re-rank the official TREC DL 19/20 re-ranking set with a pre-finetuned cross-encoder model. It will automatically download the model and data, run the re-ranking, write the results to a TREC-style run file, and report the nDCG@10 score.
@@ -41,25 +43,6 @@ lightning-ir re_rank \
41
43
42
44
For more details, see the [Usage](#usage) section.
0 commit comments