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Add files using upload-large-folder tool

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  1. README.md +5 -5
README.md CHANGED
@@ -30,7 +30,7 @@ For more information about the models, see:
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  - Assembly: hg38
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  ## Directory structure
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- - `fold_0`: Model: Cross-validation fold: Fold 0
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  - `model.chrombpnet.fold_0.encid.h5`: full chrombpnet model that combines both bias and corrected model in .h5 format
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  - `model.chrombpnet_nobias.fold_0.encid.h5`: bias-corrected accessibility model in .h5 format (Use for all biological discovery)
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  - `model.bias_scaled.fold_0.encid.h5`: bias model in .h5 format
@@ -38,10 +38,10 @@ For more information about the models, see:
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  - `model.chrombpnet_nobias.fold_0.encid.tar`: bias-corrected accessibility model in SavedModel format (Use for all biological discovery). After being untarred, it results in a directory named "chrombpnet_wo_bias".
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  - `model.bias_scaled.fold_0.encid.tar`: bias model in SavedModel format. After being untarred, it results in a directory named "bias_model_scaled".
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  - `logs.models.fold_0.encid`: folder containing log files for training models
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- - `fold_1`: Model: Cross-validation fold: Fold 1
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- - `fold_2`: Model: Cross-validation fold: Fold 2
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- - `fold_3`: Model: Cross-validation fold: Fold 3
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- - `fold_4`: Model: Cross-validation fold: Fold 4
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  # Instructions
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  ## 1. Pseudocode for loading models in .h5 format
 
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  - Assembly: hg38
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  ## Directory structure
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+ - `fold_0`: Model of 5-fold cross-validation: Fold 0
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  - `model.chrombpnet.fold_0.encid.h5`: full chrombpnet model that combines both bias and corrected model in .h5 format
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  - `model.chrombpnet_nobias.fold_0.encid.h5`: bias-corrected accessibility model in .h5 format (Use for all biological discovery)
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  - `model.bias_scaled.fold_0.encid.h5`: bias model in .h5 format
 
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  - `model.chrombpnet_nobias.fold_0.encid.tar`: bias-corrected accessibility model in SavedModel format (Use for all biological discovery). After being untarred, it results in a directory named "chrombpnet_wo_bias".
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  - `model.bias_scaled.fold_0.encid.tar`: bias model in SavedModel format. After being untarred, it results in a directory named "bias_model_scaled".
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  - `logs.models.fold_0.encid`: folder containing log files for training models
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+ - `fold_1`: Model of 5-fold coss-validation: Fold 1
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+ - `fold_2`: Model of 5-fold cross-validation: Fold 2
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+ - `fold_3`: Model of 5-fold cross-validation: Fold 3
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+ - `fold_4`: Model of 5-fold cross-validation: Fold 4
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  # Instructions
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  ## 1. Pseudocode for loading models in .h5 format