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README.md

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+---
+license: cc-by-4.0
+library_name: scvi-tools
+tags:
+- biology
+- genomics
+- single-cell
+- model_cls_name:SCVI
+- scvi_version:0.20.0
+- anndata_version:0.8.0
+- modality:rna
+- annotated:False
+---
+
+# Description
+
+scVI model trained on the full DLPFC Visium data (including the pilot samples). 
+
+# Model properties
+
+Many model properties are in the model tags. Some more are listed below.
+
+**model_init_params**:
+```json
+{
+    "n_hidden": 128,
+    "n_latent": 5,
+    "n_layers": 1,
+    "dropout_rate": 0.1,
+    "dispersion": "gene",
+    "gene_likelihood": "zinb",
+    "latent_distribution": "normal"
+}
+```
+
+**model_setup_anndata_args**:
+```json
+{
+    "layer": "counts",
+    "batch_key": "patient",
+    "labels_key": null,
+    "size_factor_key": null,
+    "categorical_covariate_keys": [
+        "sample",
+        "study"
+    ],
+    "continuous_covariate_keys": null
+}
+```
+
+**model_summary_stats**:
+|     Summary Stat Key     | Value  |
+|--------------------------|--------|
+|         n_batch          |   13   |
+|         n_cells          | 166443 |
+| n_extra_categorical_covs |   2    |
+| n_extra_continuous_covs  |   0    |
+|         n_labels         |   1    |
+|          n_vars          |  5000  |
+
+**model_data_registry**:
+|      Registry Key      |            scvi-tools Location             |
+|------------------------|--------------------------------------------|
+|           X            |           adata.layers['counts']           |
+|         batch          |          adata.obs['_scvi_batch']          |
+| extra_categorical_covs | adata.obsm['_scvi_extra_categorical_covs'] |
+|         labels         |         adata.obs['_scvi_labels']          |
+
+**model_parent_module**: scvi.model
+
+**data_is_minified**: False
+
+# Training data
+
+This is an optional link to where the training data is stored if it is too large
+to host on the huggingface Model hub.
+
+<!-- If your model is not uploaded with any data (e.g., minified data) on the Model Hub, then make
+sure to provide this field if you want users to be able to access your training data. See the scvi-tools
+documentation for details. -->
+
+Training data url: N/A
+
+# Training code
+
+This is an optional link to the code used to train the model.
+
+Training code url: N/A
+
+# References
+
+1. Maynard, Kristen R., et al. "Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex." Nature neuroscience 24.3 (2021): 425-436.
+2. Huuki-Myers, Louise A., et al. "Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex." BioRxiv (2023): 2023-02.