Dataset Viewer (First 5GB)
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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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] | 53
| 96
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1
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The Manhattan Project and its atomic bomb helped bring an end to World War II. Its legacy of peaceful uses of atomic energy continues to have an impact on history and science.
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] | 35
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| "Essay on The Manhattan Project - The Manhattan Project The Manhattan Project was to see if making a(...TRUNCATED)
| [[-0.08042721450328827,0.04698937013745308,-0.048508137464523315,0.008374293334782124,-0.06804559379(...TRUNCATED)
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| "The Manhattan Project was the name for a project conducted during World War II, to develop the firs(...TRUNCATED)
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| "versions of each volume as well as complementary websites. The first websiteâThe Manhattan Pro(...TRUNCATED)
| [[-0.0722724199295044,0.04440241679549217,-0.047262802720069885,0.003954293206334114,-0.070670880377(...TRUNCATED)
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| "The Manhattan Project. This once classified photograph features the first atomic bomb â a weap(...TRUNCATED)
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| "Nor will it attempt to substitute for the extraordinarily rich literature on the atomic bombs and t(...TRUNCATED)
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| "Manhattan Project. The Manhattan Project was a research and development undertaking during World Wa(...TRUNCATED)
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End of preview. Expand
in Data Studio
MS MARCO ColBERT Embeddings
Pre-computed ColBERT embeddings for MS MARCO using PyLate and answerdotai/answerai-colbert-small-v1.
Dataset Structure
The dataset contains:
data/corpus/: 177 parquet files with document embeddingsdata/queries/: 11 parquet files with query embeddingsdata/qrels/train.parquet: Relevance judgments (532,751 pairs)
Usage
from datasets import load_dataset
# Load from directory (recommended for large datasets)
corpus = load_dataset("parquet", data_dir="hf://datasets/WenxingZhu/msmarco_answerai_colbert_small_embeddings/data/corpus")
queries = load_dataset("parquet", data_dir="hf://datasets/WenxingZhu/msmarco_answerai_colbert_small_embeddings/data/queries")
qrels = load_dataset("parquet", data_files="hf://datasets/WenxingZhu/msmarco_answerai_colbert_small_embeddings/data/qrels/train.parquet")
Model
Generated with answerdotai/answerai-colbert-small-v1
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