add climate bert

tasks/text.py

@@ -23,6 +23,7 @@ models_descriptions = {
     "baseline": "random baseline",
     "tfidf_xgb": "TF-IDF vectorizer and XGBoost classifier",
     "bert_base_pruned": "Pruned BERT base model",
+    'climate_bert_pruned': "Fine-tuned and pruned DistilRoBERTa pre-trained on climate texts"
 }
 
 
@@ -108,7 +109,7 @@ def bert_classifier(test_dataset: dict, model: str):
 
 @router.post(ROUTE, tags=["Text Task"])
 async def evaluate_text(request: TextEvaluationRequest,
-                        model: str = "bert_base_pruned"):
+                        model: str = "climate_bert_pruned"):
     """
     Evaluate text classification for climate disinformation detection.