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L2AI-dictionary-klue-bert-base

Multiple Choice

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	---
	{}
	---

	The L2AI-dictionary model is fine-tuned checkpoint of [klue/bert-base](https://huggingface.co/klue/bert-base) for multiple choice, specifically for selecting the best dictionary definition of a given word in a sentence. Below is an example usage:

	```python
	import numpy as np
	import torch
	from transformers import AutoModelForMultipleChoice, AutoTokenizer

	model_name = "JesseStover/L2AI-dictionary-klue-bert-base"
	tokenizer = AutoTokenizer.from_pretrained(model_name)
	model = AutoModelForMultipleChoice.from_pretrained(model_name)
	model.to(torch.device("cuda" if torch.cuda.is_available() else "cpu"))

	prompts = "\"강아지는 뽀송뽀송하다.\"에 있는 \"강아지\"의 정의는 "
	candidates = [
	"\"(명사) 개의 새끼\"예요.",
	"\"(명사) 부모나 할아버지, 할머니가 자식이나 손주를 귀여워하면서 부르는 말\"이예요."
	]

	inputs = tokenizer(
	[[prompt, candidate] for candidate in candidates],
	return_tensors="pt",
	padding=True
	)

	labels = torch.tensor(0).unsqueeze(0)

	with torch.no_grad():
	outputs = model(
	**{k: v.unsqueeze(0) for k, v in inputs.items()}, labels=labels
	)

	print({i: float(x) for i, x in enumerate(outputs.logits.softmax(1)[0])})
	```

	Training data was procured under Creative Commons [CC BY-SA 2.0 KR DEED](https://creativecommons.org/licenses/by-sa/2.0/kr/) from the National Institute of Korean Language's [Basic Korean Dictionary](https://krdict.korean.go.kr) and [Standard Korean Dictionary](https://stdict.korean.go.kr/).