Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
multi-class-classification
Languages:
English
Size:
10K - 100K
| from collections import Counter | |
| from datasets import load_dataset, set_caching_enabled | |
| # If you need to force clear the cache | |
| # set_caching_enabled(False) | |
| # source = "HoC.py" | |
| source = "qanastek/HoC" | |
| dataset = load_dataset(source) | |
| # dataset = load_dataset(source, "HoC") | |
| print(dataset) | |
| f = dataset["validation"][0] | |
| print(f) | |
| print() | |
| print("#"*100) | |
| print() | |
| lengths = [] | |
| for e in dataset["train"]: | |
| l = len(e["label"]) | |
| if l == 0 or l >= 4: | |
| print(l, " => ", e, "\n") | |
| lengths.append(l) | |
| for e in dataset["validation"]: | |
| l = len(e["label"]) | |
| if l == 0 or l >= 4: | |
| print(l, " => ", e, "\n") | |
| lengths.append(l) | |
| for e in dataset["test"]: | |
| l = len(e["label"]) | |
| if l == 0 or l >= 4: | |
| print(l, " => ", e, "\n") | |
| lengths.append(l) | |
| print(Counter(lengths)) | |