Add license and pipeline tag (#3)

- Add license and pipeline tag (00134611fde156839d0275ede355a388832ec45c)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -1,21 +1,21 @@
 ---
-library_name: transformers
+base_model:
+- google-bert/bert-base-uncased
 datasets:
 - microsoft/ms_marco
 language:
 - en
-base_model:
-- google-bert/bert-base-uncased
+library_name: transformers
+pipeline_tag: feature-extraction
+license: apache-2.0
 ---
 
 # Model Card
 This is the official model from the paper [Hypencoder: Hypernetworks for Information Retrieval](https://arxiv.org/abs/2502.05364).
 
-
 ## Model Details
 This is a Hypencoder Dual Enocder. It contains two trunks the text encoder and Hypencoder. The text encoder converts items into 768 dimension vectors while the Hypencoder converts text into a small neural network which takes the 768 dimension vector from the text encoder as input. This small network is then used to output a relevance score. To use this model please take a look at the [Github](https://github.com/jfkback/hypencoder-paper) page which contains the required code and details on how to run the model.
 
-
 ### Model Variants
 We released the four models used in the paper. Each model is identical except the small neural networks, which we refer to as q-nets, have different numbers of hidden layers.