croissint を使って description を取得する

import requests
# headers = {"Authorization": f"Bearer {API_TOKEN}"}
API_URL = "https://huggingface.co/api/datasets/ibm/duorc/croissant"
def query():
    response = requests.get(API_URL)
    return response.json()
data = query()

# 1. Point to a local or remote Croissant file
import mlcroissant as mlc
url = "https://huggingface.co/api/datasets/fashion_mnist/croissant"
# 2. Inspect metadata
print(mlc.Dataset(url).metadata.to_json())
# 3. Use Croissant dataset in your ML workload
import tensorflow_datasets as tfds
builder = tfds.core.dataset_builders.CroissantBuilder(
    jsonld=url,
    record_set_ids=["record_set_fashion_mnist"],
    file_format='array_record',
)
builder.download_and_prepare()
# 4. Split for training/testing
train, test = builder.as_data_source(split=['default[:80%]', 'default[80%:]'])

t46 / fukuro-researcher

croissint を使って description を取得する #18