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  ---
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  license: mit
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  datasets:
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  - hotchpotch/JQaRA
@@ -59,7 +60,7 @@ scores = model.predict([(query, passage) for passage in passages])
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification
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  from torch.nn import Sigmoid
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- MODEL_NAME = "hotchpotch/japanese-reranker-cross-encoder-xsmall-v1
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 
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  license: mit
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  datasets:
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  - hotchpotch/JQaRA
 
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification
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  from torch.nn import Sigmoid
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+ MODEL_NAME = "hotchpotch/japanese-reranker-cross-encoder-xsmall-v1"
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)