Try Gemini 1.5 models , the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window.
Try Gemini 1.5 models , the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window.
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REST Resource: projects.locations.corpora.searchHypernyms
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Resource: SearchHypernym
Search resource: SearchHypernym. For example, { hypernym: "vehicle" hyponyms: ["sedan", "truck"] } This means in SMART_SEARCH mode, searching for "vehicle" will also return results with "sedan" or "truck" as annotations.
JSON representation
{
"name" : string ,
"hypernym" : string ,
"hyponyms" : [
string
]
}
Fields
name
string
Resource name of the SearchHypernym. Format: projects/{project_number}/locations/{location}/corpora/{corpus}/searchHypernyms/{searchHypernym}
hypernym
string
The hypernym.
hyponyms[]
string
Hyponyms that the hypernym is mapped to.
Methods
Creates a SearchHypernym inside a corpus.
Deletes a SearchHypernym inside a corpus.
Gets a SearchHypernym inside a corpus.
Lists SearchHypernyms inside a corpus.
Updates a SearchHypernym inside a corpus.
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Last updated 2023-11-15 UTC.
[{
"type": "thumb-down",
"id": "hardToUnderstand",
"label":"Hard to understand"
},{
"type": "thumb-down",
"id": "incorrectInformationOrSampleCode",
"label":"Incorrect information or sample code"
},{
"type": "thumb-down",
"id": "missingTheInformationSamplesINeed",
"label":"Missing the information/samples I need"
},{
"type": "thumb-down",
"id": "otherDown",
"label":"Other"
}]
[{
"type": "thumb-up",
"id": "easyToUnderstand",
"label":"Easy to understand"
},{
"type": "thumb-up",
"id": "solvedMyProblem",
"label":"Solved my problem"
},{
"type": "thumb-up",
"id": "otherUp",
"label":"Other"
}]
Need to tell us more?
{
"lastModified": "Last updated 2023-11-15 UTC.",
"confidential": False
}