Update README.md

README.md

@@ -26,7 +26,7 @@ pip install gliner
 ## Usage
 The example below includes all labels that the model was fine-tuned on. Although it supports extracting unseen entities, the accuracy of any other labels is not guaranteed.
 
-```
+```python
 from gliner import GLiNER
 
 model = GLiNER.from_pretrained("svilens/gliner-multitask-large-v0.5-auto-tires")
@@ -45,4 +45,19 @@ entities = model.predict_entities(text, labels)
 
 for entity in entities:
     print(entity["text"], "=>", entity["label"])
-```
+```
+
+Output:
+```
+зимни => tyre_season
+225 => tyre_width
+65 => tyre_aspect_ratio
+17 => tyre_diameter
+runflat => tyre_type
+Honda => car_make
+CR-V => car_model
+2022 => car_year
+```
+
+## Known issues
+As shown above, load index and speed rating are sometimes not properly recognized. More training examples with these two attributes are required.