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Upload README.md with huggingface_hub

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@@ -54,10 +54,10 @@ space might still be useful for analysis.
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  | Metric | Training Value | Validation Value |
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  |-------------------------|----------------|------------------|
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- | Mean Absolute Error | 0.96 | 1.00 |
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- | Pearson Correlation | 0.81 | 0.80 |
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- | Spearman Correlation | 0.82 | 0.81 |
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- | R² (R-Squared) | 0.58 | 0.56 |
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  The gene-wise coefficient of variation summarizes how well variation between different genes is
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  preserved by the generated model expression. This value is usually quite high.
@@ -66,10 +66,10 @@ preserved by the generated model expression. This value is usually quite high.
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  | Metric | Training Value |
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  |-------------------------|----------------|
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- | Mean Absolute Error | 13.59 |
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- | Pearson Correlation | 0.72 |
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- | Spearman Correlation | 0.75 |
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- | R² (R-Squared) | -0.65 |
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  </details>
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  | Index | gene_f1 | lfc_mae | lfc_pearson | lfc_spearman | roc_auc | pr_auc | n_cells |
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  | --- | --- | --- | --- | --- | --- | --- | --- |
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- | cardiac muscle cell | 0.95 | 0.51 | 0.80 | 0.98 | 0.41 | 0.93 | 7205.00 |
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- | cardiac endothelial cell | 0.99 | 1.03 | 0.74 | 0.94 | 0.31 | 0.90 | 2665.00 |
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- | hepatocyte | 0.87 | 0.72 | 0.70 | 0.96 | 0.65 | 0.94 | 1089.00 |
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- | fibroblast of cardiac tissue | 0.89 | 2.97 | 0.68 | 0.83 | 0.27 | 0.80 | 250.00 |
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- | smooth muscle cell | 0.90 | 3.57 | 0.63 | 0.76 | 0.24 | 0.81 | 222.00 |
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- | macrophage | 0.72 | 4.44 | 0.56 | 0.65 | 0.33 | 0.70 | 74.00 |
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  </details>
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@@ -186,7 +186,7 @@ scvi-tools documentation for details. -->
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  If provided by the original uploader, for those interested in understanding or replicating the
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  training process, the code is available at the link below.
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- **Training Code URL**: Not provided by uploader
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  </details>
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  | Metric | Training Value | Validation Value |
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  |-------------------------|----------------|------------------|
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+ | Mean Absolute Error | 0.98 | 1.03 |
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+ | Pearson Correlation | 0.80 | 0.80 |
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+ | Spearman Correlation | 0.82 | 0.79 |
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+ | R² (R-Squared) | 0.57 | 0.58 |
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  The gene-wise coefficient of variation summarizes how well variation between different genes is
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  preserved by the generated model expression. This value is usually quite high.
 
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  | Metric | Training Value |
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  |-------------------------|----------------|
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+ | Mean Absolute Error | 13.38 |
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+ | Pearson Correlation | 0.73 |
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+ | Spearman Correlation | 0.76 |
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+ | R² (R-Squared) | -0.63 |
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  </details>
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  | Index | gene_f1 | lfc_mae | lfc_pearson | lfc_spearman | roc_auc | pr_auc | n_cells |
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  | --- | --- | --- | --- | --- | --- | --- | --- |
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+ | cardiac muscle cell | 0.95 | 0.52 | 0.79 | 0.98 | 0.41 | 0.93 | 7205.00 |
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+ | cardiac endothelial cell | 0.98 | 1.12 | 0.68 | 0.94 | 0.31 | 0.90 | 2665.00 |
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+ | hepatocyte | 0.89 | 0.71 | 0.71 | 0.96 | 0.64 | 0.94 | 1089.00 |
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+ | fibroblast of cardiac tissue | 0.87 | 3.01 | 0.67 | 0.83 | 0.26 | 0.79 | 250.00 |
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+ | smooth muscle cell | 0.90 | 3.62 | 0.62 | 0.76 | 0.23 | 0.81 | 222.00 |
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+ | macrophage | 0.68 | 4.49 | 0.55 | 0.64 | 0.33 | 0.70 | 74.00 |
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  </details>
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  If provided by the original uploader, for those interested in understanding or replicating the
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  training process, the code is available at the link below.
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+ **Training Code URL**: https://github.com/YosefLab/scvi-hub-models/blob/main/src/scvi_hub_models/TS_train_all_tissues.ipynb
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  </details>
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