Update README.md

README.md

@@ -30,6 +30,22 @@ The dataset used to fine-tune the original pre-trained model is the [DUSHA datas
 emotions = ['neutral', 'positive', 'angry', 'sad', 'other']
 ```
 
+# How to use
+
+```python
+from transformers.pipelines import pipeline
+
+pipe = pipeline(model="KELONMYOSA/wav2vec2-xls-r-300m-emotion-ru", trust_remote_code=True)
+
+result = pipe("speech.wav")
+print(result)
+```
+~~~
+[{'label': 'neutral', 'score': 0.00318}, {'label': 'positive', 'score': 0.00376}, {'label': 'sad', 'score': 0.00145}, {'label': 'angry', 'score': 0.98984}, {'label': 'other', 'score': 0.00176}]
+~~~
+
+# Evaluation
+
 It achieves the following results:
 - Training Loss: 0.528700
 - Validation Loss: 0.349617