Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+- hu
+base_model:
+- SZTAKI-HLT/hubert-base-cc
+- FacebookAI/xlm-roberta-base
+---
+
+# 🧠 Static Word Embeddings for Hungarian (huBERT & XLM-RoBERTa)
+
+This repository contains static word embedding models extracted from the following BERT-based models:
+
+- [`SZTAKI-HLT/hubert-base-cc`](https://huggingface.co/SZTAKI-HLT/hubert-base-cc)
+- [`FacebookAI/xlm-roberta-base`](https://huggingface.co/FacebookAI/xlm-roberta-base)
+
+## 📦 Available Embedding Variants
+
+Each model is provided in three static embedding variants:
+
+- **Decontextualized**: Token embeddings extracted without any surrounding context.
+- **Aggregate**: Static embeddings computed by averaging token representations of different contexts the word appears in.
+- **X2Static**: Learned static embeddings trained via the **X2Static** method, designed to optimize static representations from contextual models.
+
+## 🧪 Use Case
+
+These embeddings were developed and evaluated as part of the paper: **_A Comparative Analysis of Static Word Embeddings for Hungarian_** by *Máté Gedeon*.
+
+They can be used for intrinsic tasks (e.g., word analogies) and extrinsic tasks (e.g., POS tagging, NER) in Hungarian NLP applications.