Create README.md

README.md

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+---
+language:
+- ko
+---
+
+The L2AI-dictionary model is fine-tuned 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/).