Update README.md

README.md

@@ -4,3 +4,30 @@ license: cc-by-nc-sa-4.0
 datasets: 
   - ClaimRev
 ---
+
+# Model
+This model was obtained by fine-tuning bert-base-cased on the ClaimRev dataset.
+
+Paper: [Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale](https://aclanthology.org/2021.eacl-main.147/)
+Authors: Gabriella Skitalinskaya, Jonas Klaff, Henning Wachsmuth
+
+# Claim Quality Classification
+We cast this task as a pairwise classification task, where the objective is to compare two versions of the same claim and determine which one is better.
+
+# Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("gabski/bert-relative-claim-quality")
+model = AutoModelForSequenceClassification.from_pretrained("gabski/bert-relative-claim-quality")
+claim_1 = 'Smoking marijuana is less harmfull then smoking cigarettes.'
+claim_2 = 'Smoking marijuana is less harmful than smoking cigarettes.'
+model_input = tokenizer(claim_1,claim_2, return_tensors='pt')
+model_outputs = model(**model_input)
+
+outputs = torch.nn.functional.softmax(model_outputs.logits, dim = -1)
+print(outputs)
+```
+