qangaroou

Références :

• Code
• Visage câlin

medhop

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:qangaroo/medhop')

• Description :

We have created two new Reading Comprehension datasets focussing on multi-hop (alias multi-step) inference.

Several pieces of information often jointly imply another fact. In multi-hop inference, a new fact is derived by combining facts via a chain of multiple steps.

Our aim is to build Reading Comprehension methods that perform multi-hop inference on text, where individual facts are spread out across different documents.

The two QAngaroo datasets provide a training and evaluation resource for such methods.

• Licence : Aucune licence connue
• Version : 1.0.0
• Divisions :

• Caractéristiques :

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masqué_medhop

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:qangaroo/masked_medhop')

• Description :

We have created two new Reading Comprehension datasets focussing on multi-hop (alias multi-step) inference.

Several pieces of information often jointly imply another fact. In multi-hop inference, a new fact is derived by combining facts via a chain of multiple steps.

Our aim is to build Reading Comprehension methods that perform multi-hop inference on text, where individual facts are spread out across different documents.

The two QAngaroo datasets provide a training and evaluation resource for such methods.

• Licence : Aucune licence connue
• Version : 1.0.0
• Divisions :

• Caractéristiques :

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}

wikihop

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:qangaroo/wikihop')

• Description :

We have created two new Reading Comprehension datasets focussing on multi-hop (alias multi-step) inference.

Several pieces of information often jointly imply another fact. In multi-hop inference, a new fact is derived by combining facts via a chain of multiple steps.

Our aim is to build Reading Comprehension methods that perform multi-hop inference on text, where individual facts are spread out across different documents.

The two QAngaroo datasets provide a training and evaluation resource for such methods.

• Licence : Aucune licence connue
• Version : 1.0.0
• Divisions :

• Caractéristiques :

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        "_type": "Value"
    },
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}

masqué_wikihop

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:qangaroo/masked_wikihop')

• Description :

We have created two new Reading Comprehension datasets focussing on multi-hop (alias multi-step) inference.

Several pieces of information often jointly imply another fact. In multi-hop inference, a new fact is derived by combining facts via a chain of multiple steps.

Our aim is to build Reading Comprehension methods that perform multi-hop inference on text, where individual facts are spread out across different documents.

The two QAngaroo datasets provide a training and evaluation resource for such methods.

• Licence : Aucune licence connue
• Version : 1.0.0
• Divisions :

• Caractéristiques :

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