Update README.md

README.md

@@ -10,6 +10,7 @@ model-index:
   results: []
 datasets:
 - stanfordnlp/coqa
+library_name: transformers
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,13 +19,14 @@ should probably proofread and complete it, then remove this comment. -->
 # apricot_binary_coqa_deberta-v3-base_for_vicuna-7b-v1.5
 
 
-This model is fine-tuned for black-box LLM calibration as part of the 🍑 Apricot paper ["Calibrating Large Language Models Using Their Generations Only"](https://github.com/parameterlab/apricot) (ACL 2024).
+This model is fine-tuned for black-box LLM calibration as part of the 🍑 Apricot paper ["Calibrating Large Language Models Using Their Generations Only"](https://arxiv.org/abs/2403.05973) (ACL 2024).
 
 ## Model description
 
 
 This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) to predict the calibration score for the [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) model on the questions from the stanfordnlp/coqa dataset. It uses the binary type of calibration target score.
 
+
 ## Intended uses & limitations
 
 More information needed