Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
multi-class-classification
Languages:
English
Size:
10K - 100K
File size: 804 Bytes
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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))
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