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: HfHubHTTPError
Message: 404 Client Error: Not Found for url: https://hf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com/repos/6a/cf/6acfb26f09a0c3e43948aee2f8a6812f7580376bf6aa6ddd468cc90597e90668/da787b6e3401d93c7fcd424bf98a0d19bfee5b84dd6f59a200079a8e4d118033?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA2JU7TKAQFN2FTF47%2F20240404%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20240404T105113Z&X-Amz-Expires=259200&X-Amz-Signature=1a4db73e184dc0031e192d1f235ff4df0fd3a726edd6aa967d977e7b4cd6fc47&X-Amz-SignedHeaders=host&response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27glaive_code_assistant_v3.json%3B%20filename%3D%22glaive_code_assistant_v3.json%22%3B&response-content-type=application%2Fjson&x-id=GetObject
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 328, in compute
compute_first_rows_from_parquet_response(
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 88, in compute_first_rows_from_parquet_response
rows_index = indexer.get_rows_index(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 631, in get_rows_index
return RowsIndex(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 512, in __init__
self.parquet_index = self._init_parquet_index(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 529, in _init_parquet_index
response = get_previous_step_or_raise(
File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 566, in get_previous_step_or_raise
raise CachedArtifactError(
libcommon.simple_cache.CachedArtifactError: The previous step failed.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_errors.py", line 304, in hf_raise_for_status
response.raise_for_status()
File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/models.py", line 1021, 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/6a/cf/6acfb26f09a0c3e43948aee2f8a6812f7580376bf6aa6ddd468cc90597e90668/da787b6e3401d93c7fcd424bf98a0d19bfee5b84dd6f59a200079a8e4d118033?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA2JU7TKAQFN2FTF47%2F20240404%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20240404T105113Z&X-Amz-Expires=259200&X-Amz-Signature=1a4db73e184dc0031e192d1f235ff4df0fd3a726edd6aa967d977e7b4cd6fc47&X-Amz-SignedHeaders=host&response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27glaive_code_assistant_v3.json%3B%20filename%3D%22glaive_code_assistant_v3.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 243, 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 2215, 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 1239, 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 1388, in __iter__
for key, example in ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1044, in __iter__
yield from islice(self.ex_iterable, self.n)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__
for key, pa_table in self.generate_tables_fn(**self.kwargs):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 107, in _generate_tables
batch = f.read(self.config.chunksize)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 342, in read_with_retries
out = read(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 1856, 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 643, in _fetch_range
hf_raise_for_status(r)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_errors.py", line 362, in hf_raise_for_status
raise HfHubHTTPError(str(e), response=response) from e
huggingface_hub.utils._errors.HfHubHTTPError: 404 Client Error: Not Found for url: https://hf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com/repos/6a/cf/6acfb26f09a0c3e43948aee2f8a6812f7580376bf6aa6ddd468cc90597e90668/da787b6e3401d93c7fcd424bf98a0d19bfee5b84dd6f59a200079a8e4d118033?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA2JU7TKAQFN2FTF47%2F20240404%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20240404T105113Z&X-Amz-Expires=259200&X-Amz-Signature=1a4db73e184dc0031e192d1f235ff4df0fd3a726edd6aa967d977e7b4cd6fc47&X-Amz-SignedHeaders=host&response-content-disposition=attachment%3B%20filename%2A%3DUTF-8%27%27glaive_code_assistant_v3.json%3B%20filename%3D%22glaive_code_assistant_v3.json%22%3B&response-content-type=application%2Fjson&x-id=GetObjectNeed help to make the dataset viewer work? Open a discussion for direct support.
Glaive-code-assistant-v2
Glaive-code-assistant-v2 is a dataset of ~1M code problems and solutions generated using Glaive’s synthetic data generation platform.
This is built on top of the previous version of the dataset that can be found here. This already includes v1 and v2 of the dataset.
To report any problems or suggestions in the data, join the Glaive discord
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