Delete testSampleCode.py with huggingface_hub

testSampleCode.py

@@ -1,67 +0,0 @@
-import pandas as pd
-from sklearn.model_selection import train_test_split
-
-dataFromCsv = pd.read_csv('test.csv')
-
-text = dataFromCsv['text'].tolist()
-label = dataFromCsv['label'].tolist()
-
-print(text)
-print(label)
-
-sorted_lable = sorted((dataFromCsv['label']).unique())
-print(sorted_lable)
-
-
-lableList = {label: i for i, label in enumerate(sorted_lable)}
-dataFromCsv['label'] = dataFromCsv['label'].map(lableList)
-
-print("label list = ",lableList)
-print("from csv file label = ",dataFromCsv['label'])
-
- 
-
-# Split the dataset 
-train_df, test_df = train_test_split(dataFromCsv, test_size=0.2, random_state=42) 
-print("Training Set:") 
-print(train_df) 
-print("\nTesting Set:") 
-print(test_df)
-
-lableList = { 0: "lastmonth", 1: "nextweek", 2: "sevendays", 3: "today", 4: "yesterday" }
-
-print("After = ", lableList[4])
-print("label items = ", lableList.items())
-
-#test of dataset
-# from torch.utils.data import Dataset
-# import torch
-
-# class IntentDataset(Dataset):
-#     def __init__(self, encodings, labels):
-#         self.encodings = encodings
-#         self.labels = labels
-
-#     def __getitem__(self, idx):
-#             item = {key: torch.tensor(val[idx]) for key, val in self.encodings.items()}
-#             label = self.labels[idx]
-#             item['labels'] = torch.tensor(self.labels[idx])
-   
-#             return item
-
-#     def __len__(self):
-#         return len(self.labels)
-
-# # Sample data 
-# encodings = { 
-#     'input_ids': [[101, 102, 103], [104, 105, 106], [107, 108, 109]], 
-#     'attention_mask': [[1, 1, 1], [1, 1, 1], [1, 1, 1]] 
-# } 
-# labels = [0, 1, 0]
-
-# dataset = IntentDataset(encodings, labels)
-# dataset_length = len(dataset) 
-# print(f"The dataset contains {dataset_length} items. {dataset.labels}")
-
-# dataset_show = dataset[2]
-# print(dataset_show)