Update README.md

README.md

@@ -15,6 +15,29 @@ The input format for the model is: "premise: GROUNDING_DOCUMENT hypothesis: HYPO
 
 The model predicts a binary label ('1' - Factualy Consistent, '0' - Factualy Inconsistent).
 
+
+## Usage example:
+```python
+from transformers import T5ForConditionalGeneration
+from transformers import T5Tokenizer
+
+model_path = 'google/t5_11b_trueteacher_and_anli'
+tokenizer = T5Tokenizer.from_pretrained(model_path)
+model = T5ForConditionalGeneration.from_pretrained(model_path)
+
+premise = 'the sun is shining'
+for hypothesis, expected in [('the sun is out in the sky', '1'), 
+                             ('the cat is shiny', '0')]:
+  input_ids = tokenizer(f'premise: {premise} hypothesis: {hypothesis}', return_tensors='pt').input_ids
+  outputs = model.generate(input_ids)
+  result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+  print(f'premise: {premise}')
+  print(f'hypothesis: {hypothesis}')
+  print(f'result: {result} (expected: {expected})\n')
+```
+
+## Citation
+
 If you use this model for a research publication, please cite the TrueTeacher paper (using the bibtex entry below) and the dataset papers mentioned above.
 
 ```