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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: HfHubHTTPError
Message: 404 Client Error: Not Found for url: https://hf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com/repos/bb/6f/bb6f3a9a37cffc43161de0ecfc1bc63e1a3a530c690a7d6b6c78cf38bc89de88/a52de4b143ce0515aa49262823e3432e525a4c3e530f6a33084522324dbb14b3?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA2JU7TKAQLC2QXPN7%2F20241106%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20241106T193239Z&X-Amz-Expires=259200&X-Amz-Signature=75a6f7908763e02379514ebb46e97beb2165fc677971faa19d2ade8a75effb56&X-Amz-SignedHeaders=host&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27meta.json%3B%20filename%3D%22meta.json%22%3B&response-content-type=application%2Fjson&x-id=GetObject
<?xml version="1.0" encoding="UTF-8"?>
<Error><Code>NoSuchKey</Code><Message>The specified key does not exist.</Message><Key>repos/bb/6f/bb6f3a9a37cffc43161de0ecfc1bc63e1a3a530c690a7d6b6c78cf38bc89de88/a52de4b143ce0515aa49262823e3432e525a4c3e530f6a33084522324dbb14b3</Key><RequestId>WTAWP6M8QQVRYM9M</RequestId><HostId>+XQlKbUa6rZr9+A9aGxrmmUUdtBl5NO9CPzyvZjCNyPAVnN7LObFKqLuLAuX8NNtFrTl+Gyyd0BOqkxx1Sd/TBCOlbPkt+L5HVSSYbPdnzk=</HostId></Error>
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_http.py", line 406, in hf_raise_for_status
response.raise_for_status()
File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/models.py", line 1024, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 404 Client Error: Not Found for url: https://hf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com/repos/bb/6f/bb6f3a9a37cffc43161de0ecfc1bc63e1a3a530c690a7d6b6c78cf38bc89de88/a52de4b143ce0515aa49262823e3432e525a4c3e530f6a33084522324dbb14b3?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA2JU7TKAQLC2QXPN7%2F20241106%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20241106T193239Z&X-Amz-Expires=259200&X-Amz-Signature=75a6f7908763e02379514ebb46e97beb2165fc677971faa19d2ade8a75effb56&X-Amz-SignedHeaders=host&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27meta.json%3B%20filename%3D%22meta.json%22%3B&response-content-type=application%2Fjson&x-id=GetObject
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 233, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2998, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1918, in _head
return _examples_to_batch(list(self.take(n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2093, in __iter__
for key, example in ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1576, in __iter__
for key_example in islice(self.ex_iterable, self.n - ex_iterable_num_taken):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__
for key, pa_table in self.generate_tables_fn(**gen_kwags):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 123, in _generate_tables
batch = f.read(self.config.chunksize)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 826, in read_with_retries
out = read(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 757, in read
return super().read(length)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 1846, in read
out = self.cache._fetch(self.loc, self.loc + length)
File "/src/services/worker/.venv/lib/python3.9/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/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 720, in _fetch_range
hf_raise_for_status(r)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_http.py", line 477, in hf_raise_for_status
raise _format(HfHubHTTPError, str(e), response) from e
huggingface_hub.errors.HfHubHTTPError: 404 Client Error: Not Found for url: https://hf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com/repos/bb/6f/bb6f3a9a37cffc43161de0ecfc1bc63e1a3a530c690a7d6b6c78cf38bc89de88/a52de4b143ce0515aa49262823e3432e525a4c3e530f6a33084522324dbb14b3?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA2JU7TKAQLC2QXPN7%2F20241106%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20241106T193239Z&X-Amz-Expires=259200&X-Amz-Signature=75a6f7908763e02379514ebb46e97beb2165fc677971faa19d2ade8a75effb56&X-Amz-SignedHeaders=host&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27meta.json%3B%20filename%3D%22meta.json%22%3B&response-content-type=application%2Fjson&x-id=GetObject
<?xml version="1.0" encoding="UTF-8"?>
<Error><Code>NoSuchKey</Code><Message>The specified key does not exist.</Message><Key>repos/bb/6f/bb6f3a9a37cffc43161de0ecfc1bc63e1a3a530c690a7d6b6c78cf38bc89de88/a52de4b143ce0515aa49262823e3432e525a4c3e530f6a33084522324dbb14b3</Key><RequestId>WTAWP6M8QQVRYM9M</RequestId><HostId>+XQlKbUa6rZr9+A9aGxrmmUUdtBl5NO9CPzyvZjCNyPAVnN7LObFKqLuLAuX8NNtFrTl+Gyyd0BOqkxx1Sd/TBCOlbPkt+L5HVSSYbPdnzk=</HostId></Error>Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for Time-300B
This repository contains the Time-300B dataset of the paper Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts.
For details on how to use this dataset, please visit our GitHub page.
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