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README.md

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+<div align="center">
+
+# ✦ Veytra ✦
+
+**From words to vectors, from vectors to meaning.**
+
+A lightweight, elegant **sentence embedding model**, built from scratch.
+
+[![Params](https://img.shields.io/badge/params-3.3M-blue)](https://github.com/coderian/veytra)
+[![Embedding](https://img.shields.io/badge/embedding-64d-green)](https://github.com/coderian/veytra)
+[![Dataset](https://img.shields.io/badge/dataset-STS--B-orange)](https://huggingface.co/datasets/sentence-transformers/stsb)
+[![GitHub](https://img.shields.io/badge/GitHub-coderian%2Fveytra-black?logo=github)](https://github.com/coderian/veytra)
+
+</div>
+
 ---
-license: mit
+
+Trained with a Transformer architecture, Veytra maps sentences into **64-dimensional vectors** and measures the **semantic closeness** between two sentences via cosine similarity. Small yet ambitious — designed for those who believe in the power of simplicity.
+
+<div align="center">
+
+| ⚙️ Architecture | |
+|---|---|
+| **Total Parameters** | ~3.3M (3,316,544) |
+| **Tokenizer** | GPT-2 (50,257 vocab) |
+| **Model** | Transformer Encoder (2 layers, 4 heads) |
+| **Embedding Dimension** | 64 |
+| **Max Length** | 64 tokens |
+| **Pooling** | Mean Pooling + L2 Normalization |
+
+</div>
+
 ---
+
+## ⚡ Usage
+
+```bash
+python3 train.py
+```
+
+<div align="center">
+
+*Veytra — encoding meaning.*
+
+</div>

veytra-embed-base.pt

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