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app.py
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@@ -1,26 +1,22 @@
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from utils import *
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import gradio as gr
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from transformers import
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def download_model():
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# 下載並快取SentenceTransformer所需的模型和tokenizer
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PreTrainedModel.from_pretrained(sentence_transformer_model)
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PreTrainedTokenizer.from_pretrained(sentence_transformer_model)
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# 下載並快取AutoTokenizer所需的模型
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biobart_model = "fuhsiao/BioBART-PMC-EXT-Section"
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PreTrainedModel.from_pretrained(biobart_model)
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AutoTokenizer.from_pretrained(biobart_model)
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AutoModel.from_pretrained(biobart_model)
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# 下載並快取AutoModelForSeq2SeqLM所需的模型
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bart_model = "fuhsiao/BART-PMC-EXT-Section"
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PreTrainedModel.from_pretrained(bart_model)
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AutoTokenizer.from_pretrained(bart_model)
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AutoModelForSeq2SeqLM.from_pretrained(bart_model)
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return True
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def main(file, ext_threshold, article_type):
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if file is None or ext_threshold is None or article_type is None:
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from utils import *
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import gradio as gr
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from sentence_transformers import SentenceTransformer
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, AutoModel
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def download_model():
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# 下載並快取SentenceTransformer所需的模型和tokenizer
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SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
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# 下載並快取AutoTokenizer所需的模型
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biobart_model = "fuhsiao/BioBART-PMC-EXT-Section"
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AutoModel.from_pretrained(biobart_model)
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AutoTokenizer.from_pretrained(biobart_model)
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# 下載並快取AutoModelForSeq2SeqLM所需的模型
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bart_model = "fuhsiao/BART-PMC-EXT-Section"
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AutoModelForSeq2SeqLM.from_pretrained(bart_model)
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AutoTokenizer.from_pretrained(bart_model)
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return True
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def main(file, ext_threshold, article_type):
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if file is None or ext_threshold is None or article_type is None:
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