Update README.md

README.md

@@ -18,7 +18,9 @@ datasets:
 
 GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.
 
-This version has been ot recognize and classify **Personally Identifiable Information** (PII) within text. The training dataset has been generated using `mistralai/Mistral-7B-Instruct-v0.2`.
+This version has been optimized to recognize and classify **Personally Identifiable Information** (PII) within text.
+
+The model has been trained by fine-tuning `urchade/gliner_multi-v2.1` on the `urchade/synthetic-pii-ner-mistral-v1` dataset.
 
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