# install huggingface_hub from the command line: # # pip install huggingface_hub # pip install datasets # # Log into huggingface hub (this only needs to be done once per project, and then it is cached) # # huggingface-cli login # # This will ask you for an access token import datasets # dataset1 # dataset2 # dataset3 # dataset3_single # dataset3_single_cv ##### dataset1 ####### dataset = datasets.load_dataset( "parquet", name = "dataset1", data_dir = "./intermediate", data_files = { "train" : "dataset1.parquet"}, cache_dir = "/scratch/maom_root/maom0/maom", keep_in_memory = True) dataset.push_to_hub( repo_id = "maom/MegaScale", config_name = "dataset1", data_dir = "dataset1/data", commit_message = "Upload dataset1") ##### dataset2 ####### dataset = datasets.load_dataset( "parquet", name = "dataset2", data_dir = "./intermediate", data_files = { "train" : "dataset2.parquet"}, cache_dir = "/scratch/maom_root/maom0/maom", keep_in_memory = True) dataset.push_to_hub( repo_id = "maom/MegaScale", config_name = "dataset2", data_dir = "dataset2/data", commit_message = "Upload dataset2") ##### dataset3 ####### dataset = datasets.load_dataset( "parquet", name = "dataset3", data_dir = "./intermediate", data_files = { "train" : "dataset3.parquet"}, cache_dir = "/scratch/maom_root/maom0/maom", keep_in_memory = True) dataset.push_to_hub( repo_id = "maom/MegaScale", config_name = "dataset3", data_dir = "dataset3/data", commit_message = "Upload dataset3") ##### dataset3_single ####### dataset = datasets.load_dataset( "parquet", name = "dataset3_single", data_dir = "./intermediate", data_files = { "train" : "dataset3_single_train.parquet", "val" : "dataset3_single_val.parquet", "test" : "dataset3_single_test.parquet"}, cache_dir = "/scratch/maom_root/maom0/maom", keep_in_memory = True) dataset.push_to_hub( repo_id = "maom/MegaScale", config_name = "dataset3_single", data_dir = "dataset3_single/data", commit_message = "Upload dataset3_single") ##### dataset3_single_cv ####### dataset = datasets.load_dataset( "parquet", name = "dataset3_single_cv", data_dir = "./intermediate", data_files = { "train_0" : "dataset3_single_cv_train_0.parquet", "train_1" : "dataset3_single_cv_train_1.parquet", "train_2" : "dataset3_single_cv_train_2.parquet", "train_3" : "dataset3_single_cv_train_3.parquet", "train_4" : "dataset3_single_cv_train_4.parquet", "val_0" : "dataset3_single_cv_val_0.parquet", "val_1" : "dataset3_single_cv_val_1.parquet", "val_2" : "dataset3_single_cv_val_2.parquet", "val_3" : "dataset3_single_cv_val_3.parquet", "val_4" : "dataset3_single_cv_val_4.parquet", "test_0" : "dataset3_single_cv_test_0.parquet", "test_1" : "dataset3_single_cv_test_1.parquet", "test_2" : "dataset3_single_cv_test_2.parquet", "test_3" : "dataset3_single_cv_test_3.parquet", "test_4" : "dataset3_single_cv_test_4.parquet"}, cache_dir = "/scratch/maom_root/maom0/maom", keep_in_memory = True) dataset.push_to_hub( repo_id = "maom/MegaScale", config_name = "dataset3_single_cv", data_dir = "datase3_single_cv/data", commit_message = "Upload dataset3_single_cv") ##### AlphaFold2_model_PDBs #### dataset = datasets.load_dataset( "parquet", name = "AlphaFold_model_PDBs", data_dir = "./intermediate", data_files = { "train" : "AlphaFold_model_PDBs.parquet"}, cache_dir = "/scratch/maom_root/maom0/maom", keep_in_memory = True) dataset.push_to_hub( repo_id = "maom/MegaScale", config_name = "AlphaFold_model_PDBs", data_dir = "AlphaFold_model_PDBs/data", commit_message = "Upload AlphaFold_model_PDBs")