Create README.md

# Overview
This is a named entity recognition model based on `knowledgator/gliner-multitask-large-v0.5`, specifically fine-tuned for automotive tire attributes extraction. The fine-tuning dataset consists of queries in Bulgarian.

# How to use?

```
from gliner import GLiNER

model = GLiNER.from_pretrained("svilens/gliner-multitask-large-v0.5-auto-tires")

text = "Търся зимни гуми 225/65 R17 91V runflat за Honda CR-V 2022"

labels = [
"tyre_size", "tyre_type", "tyre_width", "tyre_aspect_ratio", "tyre_diameter",
"tyre_load_index", "tyre_speed_rating", "tyre_type", "tyre_season",
"car_make", "car_model", "car_year"
]

entities = model.predict_entities(text, labels)

for entity in entities:
print(entity["text"], "=>", entity["label"])
```

README.md

@@ -0,0 +1,13 @@
+---
+datasets:
+- svilens/auto-tires-ner
+language:
+- en
+- bg
+base_model:
+- knowledgator/gliner-multitask-large-v0.5
+tags:
+- ner
+- automotive
+- tires
+---