Update README.md

README.md

@@ -104,8 +104,18 @@ This model was fine-tuned on the [MultiNLI](https://huggingface.co/datasets/mult
 
 The foundation model is [DeBERTa-v3-large from Microsoft](https://huggingface.co/microsoft/deberta-v3-large). DeBERTa-v3 combines several recent innovations compared to classical Masked Language Models like BERT, RoBERTa etc., see the [paper](https://arxiv.org/abs/2111.09543)
 
-## Intended uses & limitations
-#### How to use the model
+
+### How to use the model
+#### Simple zero-shot classification pipeline
+```python
+from transformers import pipeline
+classifier = pipeline("zero-shot-classification", model="MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli")
+sequence_to_classify = "Angela Merkel is a politician in Germany and leader of the CDU"
+candidate_labels = ["politics", "economy", "entertainment", "environment"]
+output = classifier(sequence_to_classify, candidate_labels, multi_label=False)
+print(output)
+```
+#### NLI use-case
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch