Add pipeline tag, library name, link to code and copy Github README

This PR ensures the model is tagged correctly, and people can find the model under the "feature-extraction" tag. It also adds the
library name to display an inferencing widget in the top right corner. It also copies the content of the Github README to the model card.

README.md

@@ -1,3 +1,32 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+pipeline_tag: feature-extraction
+library_name: transformers
+---
+
+# Set-Encoder
+
+This repository contains the code for the paper: [`Set-Encoder: Permutation-Invariant Inter-Passage Attention for Listwise Passage Re-Ranking with Cross-Encoders`](https://arxiv.org/abs/2404.06912).
+
+We use [`lightning-ir`](https://github.com/webis-de/lightning-ir) to train and fine-tune models. Download and install the library to use the code in this repository.
+
+## Model Zoo
+
+We provide the following pre-trained models:
+
+| Model Name                                                          | TREC DL 19 (BM25) | TREC DL 20 (BM25) | TREC DL 19 (ColBERTv2) | TREC DL 20 (ColBERTv2) |
+| ------------------------------------------------------------------- | ----------------- | ----------------- | ---------------------- | ---------------------- |
+| [set-encoder-base](https://huggingface.co/webis/set-encoder-base)   | 0.724             | 0.710             | 0.788                  | 0.777                  |
+| [set-encoder-large](https://huggingface.co/webis/set-encoder-large) | 0.727             | 0.735             | 0.789                  | 0.790                  |
+
+## Inference
+
+We recommend using the `lightning-ir` cli to run inference. The following command can be used to run inference using the `set-encoder-base` model on the TREC DL 19 and TREC DL 20 datasets:
+
+```bash
+lightning-ir re_rank --config configs/re-rank.yaml --config configs/set-encoder-finetuned.yaml --config configs/trec-dl.yaml
+```
+
+## Fine-Tuning
+
+WIP