Update README.md

README.md

@@ -8,41 +8,25 @@ pipeline_tag: sentence-similarity
 library_name: sentence-transformers
 ---
 
-# SentenceTransformer based on meta-llama/Llama-3.2-1B
+# Multilingual Style Representation based on meta-llama/Llama-3.2-1B
 
-This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B). It maps sentences & paragraphs to a 2048-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+This is the Style Representation model, presented in ``Leveraging Multilingual Training for Authorship Representation:
+Enhancing Generalization across Languages and Domains``.
 
-## Model Details
+The Style Representation model encodes documents written by the same author as nearby vectors in the embedding space.
+The model can be used for authorship attribution, style similarity, machine-generated text detection, and more.
+
+For training and evaluation code, refer to our repository [here](https://github.com/junghwanjkim/multilingual_aa).
 
-### Model Description
-- **Model Type:** Sentence Transformer
+## Model Details
+- **Model Type:** [Sentence Transformer](https://www.SBERT.net)
 - **Base model:** [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) <!-- at revision 4e20de362430cd3b72f300e6b0f18e50e7166e08 -->
 - **Maximum Sequence Length:** 131072 tokens
 - **Output Dimensionality:** 2048 dimensions
 - **Similarity Function:** Cosine Similarity
-<!-- - **Training Dataset:** Unknown -->
-<!-- - **Language:** Unknown -->
-<!-- - **License:** Unknown -->
-
-### Model Sources
-
-- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
-- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
-- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
-
-### Full Model Architecture
-
-```
-SentenceTransformer(
-  (0): Transformer({'max_seq_length': 131072, 'do_lower_case': False}) with Transformer model: BidirectionalLlamaModel 
-  (1): Pooling({'word_embedding_dimension': 2048, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
-)
-```
 
 ## Usage
 
-### Direct Usage (Sentence Transformers)
-
 First install the Sentence Transformers library:
 
 ```bash
@@ -72,70 +56,5 @@ print(similarities.shape)
 ```
 
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-### Direct Usage (Transformers)
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-### Downstream Usage (Sentence Transformers)
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-You can finetune this model on your own dataset.
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-## Training Details
-
-### Framework Versions
-- Python: 3.12.11
-- Sentence Transformers: 4.1.0
-- Transformers: 4.55.2
-- PyTorch: 2.7.1+cu126
-- Accelerate: 1.7.0
-- Datasets: 3.6.0
-- Tokenizers: 0.21.4
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 ## Citation
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-### BibTeX
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