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@@ -7,21 +7,6 @@ sdk: static
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  pinned: true
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  license: bsd-3-clause
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  short_description: Probabilistic modeling of single-cell omics data
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- collections:
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- - name: SCANVI
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- description: "A collection of SCANVI models."
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- - name: SCVI
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- description: "A collection of SCVI models."
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- - name: TotalVI
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- description: "A collection of TotalVI models."
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- - name: DestVI
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- description: "A collection of DestVI models."
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- - name: Stereoscope
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- description: "A collection of Stereoscope models."
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- display:
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- models: false
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- datasets: false
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- layout: collections
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  ---
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  # **scvi-tools**
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@@ -37,14 +22,19 @@ scvi-tools offers a comprehensive suite of models designed to address various ch
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  ### **Current HubModels**
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  - **[scVI](https://docs.scvi-tools.org/en/stable/user_guide/models/scvi.html)**:
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  - A variational autoencoder for dimensionality reduction, batch correction, and clustering.
 
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  - **[scANVI](https://docs.scvi-tools.org/en/stable/user_guide/models/scanvi.html)**:
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  - A semi-supervised model designed for label prediction, especially in cases of partially labeled data.
 
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  - **[totalVI](https://docs.scvi-tools.org/en/stable/user_guide/models/totalvi.html)**:
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  - A multi-modal model for joint analysis of RNA and protein data, additionally allowing imputation of missing protein data.
 
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  - **[DestVI](https://docs.scvi-tools.org/en/stable/user_guide/models/destvi.html)**:
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  - A deconvolution model for prediction of single-cell profiles given subcellular spatial transcriptomics data. We provide here pre-trained single cell models (CondSCVI).
 
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  - **[Stereoscope](https://docs.scvi-tools.org/en/stable/user_guide/models/stereoscope.html)**:
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  - A deconvolution model for prediction of cell-type composition given subcellular spatial transcriptomics data. We provide here pre-trained single cell models.
 
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  Explore the full list of models in scvi-tools in our **[user guide](https://docs.scvi-tools.org/en/stable/user_guide/index.html)**.
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  Please reach out on [discourse](https://discourse.scverse.org), if you want to add additional models to HuggingFace.
 
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  pinned: true
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  license: bsd-3-clause
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  short_description: Probabilistic modeling of single-cell omics data
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # **scvi-tools**
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  ### **Current HubModels**
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  - **[scVI](https://docs.scvi-tools.org/en/stable/user_guide/models/scvi.html)**:
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  - A variational autoencoder for dimensionality reduction, batch correction, and clustering.
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+ - See all models in [scVI collection](https://huggingface.co/collections/scvi-tools/scvi-673c2c0f2bf4163ef14d018d)
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  - **[scANVI](https://docs.scvi-tools.org/en/stable/user_guide/models/scanvi.html)**:
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  - A semi-supervised model designed for label prediction, especially in cases of partially labeled data.
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+ - See all models at [scANVI collection](https://huggingface.co/collections/scvi-tools/scanvi-673c3a4aabddf849496e9079)
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  - **[totalVI](https://docs.scvi-tools.org/en/stable/user_guide/models/totalvi.html)**:
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  - A multi-modal model for joint analysis of RNA and protein data, additionally allowing imputation of missing protein data.
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+ - See all models in [totalVI collection](https://huggingface.co/collections/scvi-tools/totalvi-673c3d67e2882005a1d180c1)
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  - **[DestVI](https://docs.scvi-tools.org/en/stable/user_guide/models/destvi.html)**:
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  - A deconvolution model for prediction of single-cell profiles given subcellular spatial transcriptomics data. We provide here pre-trained single cell models (CondSCVI).
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+ - See all models in [DestVI collection](https://huggingface.co/collections/scvi-tools/destvi-673c3dbf537347953810a215)
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  - **[Stereoscope](https://docs.scvi-tools.org/en/stable/user_guide/models/stereoscope.html)**:
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  - A deconvolution model for prediction of cell-type composition given subcellular spatial transcriptomics data. We provide here pre-trained single cell models.
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+ - See all models in [Stereoscope collection](https://huggingface.co/collections/scvi-tools/stereoscope-673c3ddcf1f9f7542b8819d6)
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  Explore the full list of models in scvi-tools in our **[user guide](https://docs.scvi-tools.org/en/stable/user_guide/index.html)**.
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  Please reach out on [discourse](https://discourse.scverse.org), if you want to add additional models to HuggingFace.