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sergiocamarap/Functional-cart-atlas-model
Functional-cart-atlas-model is a machine learning model from sergiocamarap. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for scvi-tools. The card lists the license as cc-by-4.0.
Pretrained scVI integration model for the Functional CAR-T Cell Atlas
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Updated Oct 10, 2025
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From the Hugging Face model README
Pretrained scVI integration model for the Functional CAR-T Cell Atlas
Many model properties are in the model tags. Some more are listed below.
model_init_params:
{
"n_hidden": 128,
"n_latent": 30,
"n_layers": 2,
"dropout_rate": 0.1,
"dispersion": "gene",
"gene_likelihood": "nb",
"latent_distribution": "normal"
}
model_setup_anndata_args:
{
"layer": "counts",
"batch_key": "Product_norm",
"labels_key": null,
"size_factor_key": null,
"categorical_covariate_keys": [
"orig_ident"
],
"continuous_covariate_keys": null
}
model_summary_stats:
| Summary Stat Key | Value |
|---|---|
| n_batch | 182 |
| n_cells | 414619 |
| n_extra_categorical_covs | 1 |
| n_extra_continuous_covs | 0 |
| n_labels | 1 |
| n_vars | 2000 |
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: True
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: https://doi.org/10.5281/zenodo.17213452
This is an optional link to the code used to train the model.
Training code url: https://github.com/ML4BM-Lab/Functional-cart-atlas
Reference pending - manuscript in preparation.