Update README.md

README.md

@@ -66,25 +66,6 @@ The model flags words or phrases belonging to these categories, producing BIO ta
 - Test set: 0.970 (CI: 0.970-0.971) 
 - Gold set: 0.868 (CI: 0.867-0.869)
 
-See [paper link] for full results and McNemar significance tests.
-
-## How to Use
-
-```python
-from transformers import AutoTokenizer, AutoModelForTokenClassification
-import torch
-
-tokenizer = AutoTokenizer.from_pretrained("steinunnfridriks/IceBERTBias")
-model = AutoModelForTokenClassification.from_pretrained("steinunnfridriks/IceBERTBias")
-
-text = "Þetta helvítis útlenska pakk..."
-inputs = tokenizer(text, return_tensors="pt")
-outputs = model(**inputs).logits
-predictions = torch.argmax(outputs, dim=2)
-
-print(predictions)
-```
-
 ## Relevant Information
 
 - **Base model**: [IceBERT](https://huggingface.co/mideind/IceBERT)