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The dataset viewer is not available for this dataset.
The dataset tries to import a module that is not installed.
Error code: DatasetModuleNotInstalledError
Exception: ImportError
Message: To be able to use olmer/wiki_mpnet_index, you need to install the following dependencies: faiss, sentence_transformers.
Please install them using 'pip install faiss sentence_transformers' for instance.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 55, in compute_config_names_response
for config in sorted(get_dataset_config_names(path=dataset, token=hf_token))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1495, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1464, in dataset_module_factory
return HubDatasetModuleFactoryWithScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1185, in get_module
local_imports = _download_additional_modules(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 294, in _download_additional_modules
raise ImportError(
ImportError: To be able to use olmer/wiki_mpnet_index, you need to install the following dependencies: faiss, sentence_transformers.
Please install them using 'pip install faiss sentence_transformers' for instance.Need help to make the dataset viewer work? Open a discussion for direct support.
Semantic search over the 44 million of English Wikipedia paragraphs using sentence transformers encoder.
The dataset contains:
- 43 911 155 paragraphs from 6 458 670 wikipedia articles stored in a zip archive;
- FAISS index with the embeddings;
- Retriever module for semantic search over the paragraphs.
The size of each paragraph varies from 20 to 2000 characters.
The embedding vector size is 768.
The index is 4-bit-quantized 2-level IVF16384_HNSW32 constructed with the FAISS library.
Sentence encoder: all-mpnet-base-v2.
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