wiki_dpr

Riferimenti:

psgs_w100.nq.exact

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:wiki_dpr/psgs_w100.nq.exact')
  • Descrizione :
This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model.
It contains 21M passages from wikipedia along with their DPR embeddings.
The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.
  • Licenza : nessuna licenza conosciuta
  • Versione : 0.0.0
  • Divide :
Diviso Esempi
'train' 21015300
  • Caratteristiche :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "embeddings": {
        "feature": {
            "dtype": "float32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

psgs_w100.nq.compressed

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:wiki_dpr/psgs_w100.nq.compressed')
  • Descrizione :
This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model.
It contains 21M passages from wikipedia along with their DPR embeddings.
The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.
  • Licenza : nessuna licenza conosciuta
  • Versione : 0.0.0
  • Divide :
Diviso Esempi
'train' 21015300
  • Caratteristiche :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "embeddings": {
        "feature": {
            "dtype": "float32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

psgs_w100.nq.no_index

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:wiki_dpr/psgs_w100.nq.no_index')
  • Descrizione :
This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model.
It contains 21M passages from wikipedia along with their DPR embeddings.
The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.
  • Licenza : nessuna licenza conosciuta
  • Versione : 0.0.0
  • Divide :
Diviso Esempi
'train' 21015300
  • Caratteristiche :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "embeddings": {
        "feature": {
            "dtype": "float32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

psgs_w100.multiset.exact

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:wiki_dpr/psgs_w100.multiset.exact')
  • Descrizione :
This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model.
It contains 21M passages from wikipedia along with their DPR embeddings.
The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.
  • Licenza : nessuna licenza conosciuta
  • Versione : 0.0.0
  • Divide :
Diviso Esempi
'train' 21015300
  • Caratteristiche :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "embeddings": {
        "feature": {
            "dtype": "float32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

psgs_w100.multiset.compressed

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:wiki_dpr/psgs_w100.multiset.compressed')
  • Descrizione :
This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model.
It contains 21M passages from wikipedia along with their DPR embeddings.
The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.
  • Licenza : nessuna licenza conosciuta
  • Versione : 0.0.0
  • Divide :
Diviso Esempi
'train' 21015300
  • Caratteristiche :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "embeddings": {
        "feature": {
            "dtype": "float32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

psgs_w100.multiset.no_index

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:wiki_dpr/psgs_w100.multiset.no_index')
  • Descrizione :
This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model.
It contains 21M passages from wikipedia along with their DPR embeddings.
The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.
  • Licenza : nessuna licenza conosciuta
  • Versione : 0.0.0
  • Divide :
Diviso Esempi
'train' 21015300
  • Caratteristiche :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "embeddings": {
        "feature": {
            "dtype": "float32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}