Update README.md

README.md

@@ -7,13 +7,11 @@ base_model:
 pipeline_tag: text-classification
 ---
 
-# SI-BERT
+# SIP-BERT
 
-**SI-BERT** is a transformer-based model designed to detect **social inequality** in German texts.  
+**SIP-BERT** is a transformer-based model designed to detect **social inequality** in German texts.  
 It was fine-tuned on **German Bundestag debates** (sourced from [OpenDiscourse](https://doi.org/10.7910/DVN/FIKIBO)), where each training instance consists of 3-sentence segments.
 
-This model was developed as part of a research project and is described in more detail in our paper: [Paper on SI-BERT (forthcoming)](https://example.com/si-bert-paper).
-
 ---
 
 ## Model Description
@@ -52,10 +50,9 @@ You can load the model with the Hugging Face `transformers` library:
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-tokenizer = AutoTokenizer.from_pretrained("miriamex/SI-BERT")
-model = AutoModelForSequenceClassification.from_pretrained("miriamex/SI-BERT")
+tokenizer = AutoTokenizer.from_pretrained("miriamex/SIP-BERT")
+model = AutoModelForSequenceClassification.from_pretrained("miriamex/SIP-BERT")
 
 inputs = tokenizer("Hier ein Beispieltext über soziale Ungleichheit.", return_tensors="pt")
 outputs = model(**inputs)
-```
-
+```