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README.md

@@ -414,7 +414,7 @@ If you use this model, please cite:
 ```bibtex
 @misc{gemma-deposium-768d,
   title={Gemma-Deposium-768D: Fast Static Embeddings from EmbeddingGemma-300M},
-  author={TSS Deposium},
+  author={The Seed Ship},
   year={2025},
   publisher={Hugging Face},
   howpublished={\url{https://huggingface.co/tss-deposium/gemma-deposium-768d}}
@@ -444,7 +444,7 @@ This model inherits the license from google/embeddinggemma-300m. Please refer to
 
 - **Google DeepMind** for the original EmbeddingGemma-300M model
 - **MinishLab** (Stephan Tulkens & Thomas van Dongen) for the Model2Vec distillation framework
-- **TSS Deposium** for benchmarking and optimization
+- **The Seed Ship** for benchmarking and optimization
 
 ## 🐛 Known Issues
 
@@ -468,4 +468,4 @@ This model inherits the license from google/embeddinggemma-300m. Please refer to
 **Quality**: GOOD (0.659 overall)
 **Recommendation**: Deploy for speed-critical multilingual search on CPU
 
-**Questions?** Open an issue on [GitHub](https://github.com/theseedship/deposium_embeddings-turbov2) or contact TSS Deposium.
+**Questions?** Open an issue on [GitHub](https://github.com/theseedship/deposium_embeddings-turbov2) or contact The Seed Ship.