research-backup/flan-t5-base-analogy-permutation

widget:

• —text: "generate analogy: mammal is to whale" example_title: "Analogy Example 1 (semantic relation)"
• —text: "generate analogy: wedding is to marriage" example_title: "Analogy Example 1 (semantic relation, metaphor)"
• —text: "generate analogy: London is to U.K." example_title: "Analogy Example 2 (entity)"
• —text: "generate analogy: actual is to actually" example_title: "Analogy Example 3 (morphological)" ---

relbert/flan-t5-base-analogy-permutation

This is google/flan-t5-base fine-tuned on relbert/semeval2012_relational_similarity for analogy generation, which is to generate a word pair (eg. bird is to crow) given a query (eg. mammal is to whale) so that the query and the generated word pair form an analogy statement.

Usage

from transformers import pipeline

pipe = pipeline('text2text-generation', model="relbert/flan-t5-base-analogy-permutation")
output = pipe("generate analogy: mammal is to whale")
print(output)
>>> [{'generated_text': 'bird is to crow'}]