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+ *.zst filter=lfs diff=lfs merge=lfs -text
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+ .venv
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+ .mypy_cache
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+ ---
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+ language:
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+ - en
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+ license: apache-2.0
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+ tags:
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+ - text
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+ pretty_name: "BFHND: Big Hard Negatives Dataset (1M sample)"
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+ size_categories:
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+ - "100K<n<1M"
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+ source_datasets:
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+ - "BeIR"
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+ task_categories:
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+ - sentence-similarity
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+ dataset_info:
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+ config_name: default
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+ features:
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+ - name: query
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+ dtype: string
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+ - name: positive
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+ sequence: string
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+ - name: negative
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+ sequence: string
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+ splits:
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+ - name: train
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+ num_bytes: 226515502
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+ num_examples: 1000000
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+ train-eval-index:
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+ - config: default
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+ task: sentence-similarity
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+ splits:
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+ train_split: train
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: "data/train/*"
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+ ---
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+
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+ # Big Hard Negatives Dataset
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+
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+ A dataset for training embedding models for semantic search.
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+
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+ TODO: add desc
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+
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+ A dataset in a [nixietune](https://github.com/nixiesearch/nixietune) compatible format:
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+
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+ ```json
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+ {
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+ "query": ")what was the immediate impact of the success of the manhattan project?",
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+ "pos": [
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+ "The presence of communication amid scientific minds was equally important to the success of the Manhattan Project as scientific intellect was. The only cloud hanging over the impressive achievement of the atomic researchers and engineers is what their success truly meant; hundreds of thousands of innocent lives obliterated."
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+ ],
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+ "neg": [
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+ "Abstract. The pivotal engineering and scientific success of the Twentieth century was the Manhattan Project. The Manhattan Project assimilated concepts and leaders from all scientific fields and engineering disciplines to construct the first two atomic bombs.",
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+ "The pivotal engineering and scientific success of the Twentieth century was the Manhattan Project. The Manhattan Project assimilated concepts and leaders from all scientific fields and engineering disciplines to construct the first two atomic bombs."
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+ ]
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+ }
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+ ```
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+
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+ ## Usage
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+
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+ To use with HF datasets:
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+
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+ ```bash
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+ pip install datasets zstandard
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+ ```
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ data = load_dataset('nixiesearch/bfhardneg-small')
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+ print(data["train"].features)
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+ ```
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+
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+ ## License
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+
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+ Apache 2.0
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