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@@ -73,9 +73,11 @@ and load one of the `HematoxLong2022` datasets, e.g.,
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  >>> HematoxLong2022 = datasets.load_dataset("maomlab/HematoxLong2022", name = "HematoxLong2022")
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  Downloading readme: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4.24/4.24 [00:00<00:00, 35.1kkB/s]
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- Downloading data: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 129/129 [00:00<00:00, 1.02MkB/s]
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- Generating test split: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1.33k/1.33k [00:00<00:00, 12705.92 examples/s]
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- Generating train split: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 442/442 [00:00<00:00, 43895.91 examples/s]
 
 
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  Generating validation split: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 610/610 [00:00<00:00, 20229.02 examples/s]
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  and inspecting the loaded dataset
@@ -90,6 +92,7 @@ and inspecting the loaded dataset
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  train: Dataset({
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  features: ['canonical SMILES', 'label'],
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  num_rows: 1330
 
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  validation: Dataset({
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  features: ['canonical SMILES', 'Label'],
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  num_rows: 610
 
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  >>> HematoxLong2022 = datasets.load_dataset("maomlab/HematoxLong2022", name = "HematoxLong2022")
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  Downloading readme: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4.24/4.24 [00:00<00:00, 35.1kkB/s]
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+ Downloading data: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 24.0k/24.0k [00:00<00:00, 155kB/s]
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+ Downloading data: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 71.9k/71.9k [00:00<00:00, 587kB/s]
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+ Downloading data: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 33.0k/33.0k [00:00<00:00, 469kB/s]
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+ Generating test split: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 442/442 [00:00<00:00, 12705.92 examples/s]
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+ Generating train split: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1.33k/1.33k [00:00<00:00, 43895.91 examples/s]
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  Generating validation split: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 610/610 [00:00<00:00, 20229.02 examples/s]
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  and inspecting the loaded dataset
 
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  train: Dataset({
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  features: ['canonical SMILES', 'label'],
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  num_rows: 1330
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+ })
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  validation: Dataset({
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  features: ['canonical SMILES', 'Label'],
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  num_rows: 610