The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: ReadTimeout
Message: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 33f1e91b-8c1e-49d7-9030-b6c9929afda1)')
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1031, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 996, in dataset_module_factory
return HubDatasetModuleFactory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 591, in get_module
standalone_yaml_path = cached_path(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 167, in cached_path
resolved_path = huggingface_hub.HfFileSystem(
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 198, in resolve_path
repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 125, in _repo_and_revision_exist
self._api.repo_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 2816, in repo_info
return method(
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 2673, in dataset_info
r = get_session().get(path, headers=headers, timeout=timeout, params=params)
File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 602, in get
return self.request("GET", url, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 589, in request
resp = self.send(prep, **send_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 703, in send
r = adapter.send(request, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_http.py", line 96, in send
return super().send(request, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/adapters.py", line 635, in send
raise ReadTimeout(e, request=request)
requests.exceptions.ReadTimeout: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 33f1e91b-8c1e-49d7-9030-b6c9929afda1)')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 MSE-text-img-dataset
We have created a custom dataset that is extracted as a subset of the Math Stack Exchange (MSE) dataset. This text-image dataset contains 64,860 questions with their respective list of answers, scores, acceptance marking, and image versions of each question and answer generated from the stored text with embedded LaTeX math markup. In this dataset there are 117,380 answers in total, with 1.81 answers per question on average. Each image was rendered from the question and answer text as it would appear in an equivalent PDF document, and the question answers selected were the first 64,860 questions and equivalent answers found in the original MSE dataset. Each question and associated answers are stored in JSON, with a JSON file for the test, train, and validation datasets. The text-image dataset has been split by 90% for training, 5% for testing, and 5% for validation. There are three image directories for the test, training, and validation images respectively, with each question’s image directory labeled by question ID from the JSON files, and each answer image by the answer ID with the question image simply labeled as ”question”.
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