Update README.md

README.md

@@ -1,14 +1,49 @@
----
-language: 
-- multilingual
-- pl
-- ru
-- uk
-- bg
-- cs
-- sl
-datasets:
-- SlavicNER
-
-license: apache-2.0
----
+---
+language:
+- multilingual
+- pl
+- ru
+- uk
+- bg
+- cs
+- sl
+datasets:
+- SlavicNER
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text2text-generation
+tags:
+- entity linking
+widget:
+  - text: "pl:Polsce"
+  - text: "cs:Velké Británii"
+  - text: "bg:българите"
+  - text: "ru:Великобританию"
+  - text: "sl:evropske komisije"
+  - text: "uk:Європейського агентства лікарських засобів"
+---
+
+# Model description
+
+This is a baseline model for named entity **lemmatization** trained on the single-out topic split of the 
+[SlavicNER corpus](https://github.com/SlavicNLP/SlavicNER).
+
+
+# Usage
+
+You can use this model directly with a pipeline for text2text generation:
+
+```python
+from transformers import pipeline
+
+model_name = "SlavicNLP/slavicner-linking-single-out-large"
+pipe = pipeline("text2text-generation", model_name)
+
+texts = ["pl:Polsce", "cs:Velké Británii", "bg:българите", "ru:Великобританию", "sl:evropske komisije",
+         "uk:Європейського агентства лікарських засобів"]
+
+outputs = pipe(texts)
+
+ids = [o['generated_text'] for o in outputs]
+print(ids)
+# ['GPE-Poland', 'GPE-Great-Britain', 'GPE-Bulgaria', 'GPE-Great-Britain', 'ORG-European-Commission', 'ORG-EMA-European-Medicines-Agency']