Update README.md

README.md

@@ -1,17 +1,12 @@
 ---
-library_name: transformers
-license: apache-2.0
-base_model: google-t5/t5-base
-tags:
-- generated_from_trainer
-metrics:
-- rouge
-model-index:
-- name: PreDA_t5-base
-  results: []
+license: cc0-1.0
 language:
 - en
-pipeline_tag: text2text-generation
+metrics:
+- rouge
+base_model:
+- google-t5/t5-base
+library_name: transformers
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -146,8 +141,8 @@ for decode_dream in output:
 ```
 
 # Dual-Use Implication
-Upon evaluation we identified no dual-use implication for the present model
+Upon evaluation we identified no dual-use implication for the present model.  The model parameters, including the weights are available under CC0 1.0 Public Domain Dedication.
 
 # Cite
 Please note that the paper referring to this model, titled PreDA: Prefix-Based Dream Reports Annotation
-with Generative Language Models, has been accepted for publication at LOD 2025 conference and will appear in the conference proceedings.
+with Generative Language Models, has been accepted for publication at LOD 2025 conference and will appear in the conference proceedings.