Dataset Viewer
The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code: ConfigNamesError
Exception: ReadTimeout
Message: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: ef57c071-b76a-49db-8f0f-8ec97e8aa725)')
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 164, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1731, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1688, in dataset_module_factory
return HubDatasetModuleFactoryWithoutScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1026, in get_module
standalone_yaml_path = cached_path(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 178, 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 2704, 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 2561, 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 93, 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: ef57c071-b76a-49db-8f0f-8ec97e8aa725)')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.
This is the sample vectorized data of the RAG part used by our SLMP platform, which contains 7805 files and corresponding vectors. The total data size is about 54GB. You can download it and store it in the langchain-ChatGLM/knowledge_base folder.
Please note that we are using version 0.2.x. The latest version is 0.3.x, which needs to be stored in Langchain-Chatchat/DATA/knowledge_base
Citation
Please cite the following paper if you use this code in your work.
@INPROCEEDINGS{10884340,
author={Guo, Menghao and Jiang, Jinling and Wu, Fan and Sun, Shanxin and Zhang, Chen and Li, Wenhui and Sun, Zeyi and Chen, Guangyong and Wu, Xindong},
booktitle={2024 IEEE International Conference on Knowledge Graph (ICKG)},
title={SLMP: A Scientific Literature Management Platform Based on Large Language Models},
year={2024},
volume={},
number={},
pages={104-109},
keywords={Training;Large language models;Knowledge graphs;Information retrieval;Data models;Question answering (information retrieval);Large Language Model;Literature Management and Retrieval;Question Answering},
doi={10.1109/ICKG63256.2024.00021}}
- Downloads last month
- 4,266