Update README.md

README.md

@@ -23,9 +23,9 @@ scvi-tools offers a comprehensive suite of models designed to address various ch
 - **[scVI](https://docs.scvi-tools.org/en/stable/user_guide/models/scvi.html)**:
   - A variational autoencoder for dimensionality reduction, batch correction, and clustering.
   - Ideal for processing single-cell RNA-seq data.
-- **[SCANVI](https://docs.scvi-tools.org/en/stable/user_guide/models/scanvi.html)**:
+- **[scANVI](https://docs.scvi-tools.org/en/stable/user_guide/models/scanvi.html)**:
   - A semi-supervised model designed for label prediction, especially in cases of partially labeled data.
-- **[TOTALVI](https://docs.scvi-tools.org/en/stable/user_guide/models/totalvi.html)**:
+- **[totalVI](https://docs.scvi-tools.org/en/stable/user_guide/models/totalvi.html)**:
   - A multi-modal model for joint analysis of RNA and protein data, additionally allowing imputation of missing protein data.
 - **[MultiVI](https://docs.scvi-tools.org/en/stable/user_guide/models/multivi.html)**:
   - A multi-modal model for joint analysis of RNA, ATAC and protein data, enabling integrative insights from diverse omics data.