Datasets:
License:
Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ConnectionError
Message: Server Disconnected
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.12/site-packages/urllib3/connection.py", line 198, in _new_conn
sock = connection.create_connection(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/urllib3/util/connection.py", line 85, in create_connection
raise err
File "/src/services/worker/.venv/lib/python3.12/site-packages/urllib3/util/connection.py", line 73, in create_connection
sock.connect(sa)
TimeoutError: timed out
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.12/site-packages/urllib3/connectionpool.py", line 787, in urlopen
response = self._make_request(
^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/urllib3/connectionpool.py", line 488, in _make_request
raise new_e
File "/src/services/worker/.venv/lib/python3.12/site-packages/urllib3/connectionpool.py", line 464, in _make_request
self._validate_conn(conn)
File "/src/services/worker/.venv/lib/python3.12/site-packages/urllib3/connectionpool.py", line 1093, in _validate_conn
conn.connect()
File "/src/services/worker/.venv/lib/python3.12/site-packages/urllib3/connection.py", line 753, in connect
self.sock = sock = self._new_conn()
^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/urllib3/connection.py", line 207, in _new_conn
raise ConnectTimeoutError(
urllib3.exceptions.ConnectTimeoutError: (<urllib3.connection.HTTPSConnection object at 0x7f8722d2bda0>, 'Connection to cas-bridge-direct.xethub.hf.co timed out. (connect timeout=10)')
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.12/site-packages/requests/adapters.py", line 644, in send
resp = conn.urlopen(
^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/urllib3/connectionpool.py", line 841, in urlopen
retries = retries.increment(
^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/urllib3/util/retry.py", line 519, in increment
raise MaxRetryError(_pool, url, reason) from reason # type: ignore[arg-type]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='cas-bridge-direct.xethub.hf.co', port=443): Max retries exceeded with url: /xet-bridge-us/68f65c36d6ad15af4b69f12a/0ae0a6d5c7a7950ff4cd4430d344c382a12bf36ae639ef86749ec07340e3409a?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=cas%2F20251020%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20251020T182906Z&X-Amz-Expires=3600&X-Amz-Signature=5e70fbb3e97c10110b4843d741d48b4102485bc7a962457c8a463b4a4e759f76&X-Amz-SignedHeaders=host&X-Xet-Cas-Uid=app%3A6241c288797aadd4ac9dd1a9&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27dataset.jsonl%3B%20filename%3D%22dataset.jsonl%22%3B&x-id=GetObject (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x7f8722d2bda0>, 'Connection to cas-bridge-direct.xethub.hf.co timed out. (connect timeout=10)'))
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 813, in read_with_retries
out = read(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 1015, in read
return super().read(length)
^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/fsspec/spec.py", line 1846, in read
out = self.cache._fetch(self.loc, self.loc + length)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/fsspec/caching.py", line 189, in _fetch
self.cache = self.fetcher(start, end) # new block replaces old
^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 969, in _fetch_range
r = http_backoff(
^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/huggingface_hub/utils/_http.py", line 329, in http_backoff
raise err
File "/src/services/worker/.venv/lib/python3.12/site-packages/huggingface_hub/utils/_http.py", line 310, in http_backoff
response = session.request(method=method, url=url, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/requests/sessions.py", line 589, in request
resp = self.send(prep, **send_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/requests/sessions.py", line 724, in send
history = [resp for resp in gen]
^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/requests/sessions.py", line 265, in resolve_redirects
resp = self.send(
^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/requests/sessions.py", line 703, in send
r = adapter.send(request, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/huggingface_hub/utils/_http.py", line 96, in send
return super().send(request, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/requests/adapters.py", line 665, in send
raise ConnectTimeout(e, request=request)
requests.exceptions.ConnectTimeout: (MaxRetryError("HTTPSConnectionPool(host='cas-bridge-direct.xethub.hf.co', port=443): Max retries exceeded with url: /xet-bridge-us/68f65c36d6ad15af4b69f12a/0ae0a6d5c7a7950ff4cd4430d344c382a12bf36ae639ef86749ec07340e3409a?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=cas%2F20251020%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20251020T182906Z&X-Amz-Expires=3600&X-Amz-Signature=5e70fbb3e97c10110b4843d741d48b4102485bc7a962457c8a463b4a4e759f76&X-Amz-SignedHeaders=host&X-Xet-Cas-Uid=app%3A6241c288797aadd4ac9dd1a9&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27dataset.jsonl%3B%20filename%3D%22dataset.jsonl%22%3B&x-id=GetObject (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x7f8722d2bda0>, 'Connection to cas-bridge-direct.xethub.hf.co timed out. (connect timeout=10)'))"), '(Request ID: 2d785a54-842b-458b-9ffa-784de129f3af)')
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
for key, example in iterator:
^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 503, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 350, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 137, in _generate_tables
batch = f.read(self.config.chunksize)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/.venv/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 827, in read_with_retries
raise ConnectionError("Server Disconnected") from disconnect_err
ConnectionError: Server DisconnectedNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
唐詩三百首 Dataset
A structured JSON dataset of 320 classical Tang Dynasty poems, sourced from 維基文庫（Wikisource）.
This dataset provides clean, machine-readable text data suitable for natural language processing (NLP), classical Chinese analysis, digital humanities, and poetry generation tasks.
📘 Overview
- Total entries: 320
- Source: Wikisource (Traditional Chinese)
- Format: JSON Lines (
.jsonl) - Encoding: UTF-8
- Language: Classical Chinese (繁體中文)
Each entry corresponds to one poem (or a poem segment) from the anthology 唐詩三百首.
🧩 Data Structure
Each poem entry contains three fields:
| Field | Type | Description |
|---|---|---|
source |
string (URL) | Original Wikisource page for that poem. |
header |
string | Original title block, including poem title, part number, and author as shown on Wikisource. |
content |
array of strings | Poem text, preserving line breaks and punctuation. Each array element is a stanza or complete poem text. |
Example
{
"source": "https://zh.wikisource.org/wiki/%E6%A5%93%E6%A9%8B%E5%A4%9C%E6%B3%8A",
"header": "楓橋夜泊\n〈\n一作夜泊楓江\n〉\n作者：\n張繼\n唐",
"content": "月落烏啼霜滿天，江楓漁火對愁眠。\n姑蘇城外寒山寺，夜半鐘聲到客船。"
}
📚 Source & Attribution
All poems are sourced from the public domain Wikisource collection:
The Wikisource text is based on the Qing edition of 唐詩三百首 and is freely available for non-commercial and academic use.
🧠 Suggested Uses
- NLP model fine-tuning on Classical Chinese
- Rhyme scheme and tonal analysis
- Poetic structure and stylistic studies
- Educational and literary visualization projects
🪪 License
- Text content: Public domain (via Wikisource)
- Dataset structure and formatting: Apache 2.0
✨ Acknowledgments
This dataset was compiled from open public domain sources to support cultural preservation and computational literature research.
- Downloads last month
- 27