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@@ -19,7 +19,7 @@ The learned low-dimensional latent representation of the data can be used for vi
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  clustering.
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  scVI takes as input a scRNA-seq gene expression matrix with cells and genes.
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- We provide an extensive [user guide](https://docs.scvi-tools.org/en/1.2.0/user_guide/models/scvi.html).
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  - See our original manuscript for further details of the model:
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  [scVI manuscript](https://www.nature.com/articles/s41592-018-0229-2).
@@ -27,7 +27,7 @@ We provide an extensive [user guide](https://docs.scvi-tools.org/en/1.2.0/user_g
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  to leverage pre-trained models.
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  This model can be used for fine tuning on new data using our Arches framework:
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- [Arches tutorial](https://docs.scvi-tools.org/en/1.0.0/tutorials/notebooks/scarches_scvi_tools.html).
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  # Model Description
 
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  clustering.
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  scVI takes as input a scRNA-seq gene expression matrix with cells and genes.
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+ We provide an extensive [user guide](https://docs.scvi-tools.org/en/stable/user_guide/models/scvi.html).
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  - See our original manuscript for further details of the model:
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  [scVI manuscript](https://www.nature.com/articles/s41592-018-0229-2).
 
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  to leverage pre-trained models.
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  This model can be used for fine tuning on new data using our Arches framework:
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+ [Arches tutorial](https://docs.scvi-tools.org/en/stable/tutorials/notebooks/scrna/scarches_scvi_tools.html).
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  # Model Description