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Upload README.md with huggingface_hub
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README.md
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---
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license: cc-by-4.0
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library_name: scvi-tools
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tags:
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- biology
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- genomics
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- single-cell
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- model_cls_name:SCANVI
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- scvi_version:0.20.0
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- anndata_version:0.8.0
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- modality:rna
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- tissue:Bladder
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- annotated:True
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---
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# Description
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Tabula sapiens. An across organ dataset of cell-types in human tissues.
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# Model properties
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Many model properties are in the model tags. Some more are listed below.
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**model_init_params**:
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```json
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{
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"n_hidden": 128,
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"n_latent": 20,
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"n_layers": 3,
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"dropout_rate": 0.05,
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"dispersion": "gene",
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"gene_likelihood": "nb",
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"latent_distribution": "normal",
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"use_batch_norm": "none",
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"use_layer_norm": "both",
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"encode_covariates": true
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}
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```
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**model_setup_anndata_args**:
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```json
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{
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"labels_key": "cell_ontology_class",
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"unlabeled_category": "unknown",
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"layer": null,
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"batch_key": "donor_assay",
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"size_factor_key": null,
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"categorical_covariate_keys": null,
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"continuous_covariate_keys": null
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}
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```
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**model_summary_stats**:
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| Summary Stat Key | Value |
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|--------------------------|-------|
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| n_batch | 5 |
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| n_cells | 24583 |
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| n_extra_categorical_covs | 0 |
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| n_extra_continuous_covs | 0 |
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| n_labels | 16 |
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| n_latent_qzm | 20 |
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| n_latent_qzv | 20 |
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| n_vars | 4000 |
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**model_data_registry**:
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| Registry Key | scvi-tools Location |
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|-------------------|----------------------------------------|
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| X | adata.X |
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| batch | adata.obs['_scvi_batch'] |
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| labels | adata.obs['_scvi_labels'] |
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| latent_qzm | adata.obsm['_scanvi_latent_qzm'] |
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| latent_qzv | adata.obsm['_scanvi_latent_qzv'] |
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| minify_type | adata.uns['_scvi_adata_minify_type'] |
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| observed_lib_size | adata.obs['_scanvi_observed_lib_size'] |
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**model_parent_module**: scvi.model
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**data_is_minified**: True
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# Training data
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This is an optional link to where the training data is stored if it is too large
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to host on the huggingface Model hub.
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<!-- If your model is not uploaded with any data (e.g., minified data) on the Model Hub, then make
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sure to provide this field if you want users to be able to access your training data. See the scvi-tools
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documentation for details. -->
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Training data url: https://zenodo.org/api/files/c676cd14-97a7-4ea6-ba70-2c7faa1d61d8/Bladder_training_data.h5ad
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# Training code
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This is an optional link to the code used to train the model.
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Training code url: https://github.com/scvi-hub-references/tabula_sapiens/main.py
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# References
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The Tabula Sapiens: A multi-organ, single-cell transcriptomic atlas of humans. The Tabula Sapiens Consortium. Science 2022.05.13; doi: https: //doi.org/10.1126/science.abl4896
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