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muhammadravi251001/multilingual-nli-dataset

Use it like this. from datasets import load_dataset, Dataset, DatasetDict import pandas as pd data_files = {"train": "multilingual_nli_train_df.csv", "validation": "multilingual_nli_validation_df.csv", "test": "multilingual_nli_test_df.csv"} dataset = load_dataset("muhammadravi251001/multilingual-nli-dataset", data_files=data_files) selected_columns = ["premise", "hypothesis", "label"] # selected_columns = dataset.column_names['train'] # Uncomment this line to… See the full description on the dataset page: https://huggingface.co/datasets/muhammadravi251001/multilingual-nli-dataset.

sourceHugging Faceopenrailupdated 3y agoView on Hugging Face

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Use it like this.

from datasets import load_dataset, Dataset, DatasetDict
import pandas as pd

data_files = {"train": "multilingual_nli_train_df.csv", 
              "validation": "multilingual_nli_validation_df.csv", 
              "test": "multilingual_nli_test_df.csv"}

dataset = load_dataset("muhammadravi251001/multilingual-nli-dataset", data_files=data_files)

selected_columns = ["premise", "hypothesis", "label"]
# selected_columns = dataset.column_names['train'] # Uncomment this line to retrieve all of the columns

df_train = pd.DataFrame(dataset["train"])
df_train = df_train[selected_columns]

df_val = pd.DataFrame(dataset["validation"])
df_val = df_val[selected_columns]

df_test = pd.DataFrame(dataset["test"])
df_test = df_test[selected_columns]

train_dataset = Dataset.from_dict(df_train)
validation_dataset = Dataset.from_dict(df_val)
test_dataset = Dataset.from_dict(df_test)

dataset = DatasetDict({"train": train_dataset, "validation": validation_dataset, "test": test_dataset})

df_multilingual_train = pd.DataFrame(dataset['train'])
df_multilingual_validation = pd.DataFrame(dataset['validation'])
df_multilingual_test = pd.DataFrame(dataset['test'])