Update app.py
Browse files
app.py
CHANGED
@@ -15,17 +15,17 @@ st.write("This tool lets you extract relation triples concerning interactions be
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st.write("It is the result of an end of studies project within ESI school and dedicated to biomedical researchers looking to extract precise information about the subject without digging into long publications.")
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@st.cache(
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def load_tokenizer():
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return AutoTokenizer.from_pretrained("dmis-lab/biobert-large-cased-v1.1", truncation = True, padding=True, model_max_length=512,)
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tokenizer = load_tokenizer()
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@st.cache(
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def load_modelNER(tokenizer):
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model_checkpoint = BertForTokenClassification.from_pretrained("dexay/Ner2HgF", )
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return pipeline("token-classification", tokenizer = tokenizer,model=model_checkpoint, )
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@st.cache(
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def load_modelRE(tokenizer):
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model_re = AutoModelForSequenceClassification.from_pretrained("dexay/reDs3others", )
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return pipeline("text-classification", tokenizer = tokenizer,model=model_re, )
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st.write("It is the result of an end of studies project within ESI school and dedicated to biomedical researchers looking to extract precise information about the subject without digging into long publications.")
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@st.cache(hash_funcs={tokenizers.Tokenizer: lambda _: None, tokenizers.AddedToken: lambda _: None})
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def load_tokenizer():
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return AutoTokenizer.from_pretrained("dmis-lab/biobert-large-cased-v1.1", truncation = True, padding=True, model_max_length=512,)
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tokenizer = load_tokenizer()
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@st.cache(hash_funcs={tokenizers.Tokenizer: lambda _: None, tokenizers.AddedToken: lambda _: None})
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def load_modelNER(tokenizer):
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model_checkpoint = BertForTokenClassification.from_pretrained("dexay/Ner2HgF", )
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return pipeline("token-classification", tokenizer = tokenizer,model=model_checkpoint, )
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+
@st.cache(hash_funcs={tokenizers.Tokenizer: lambda _: None, tokenizers.AddedToken: lambda _: None})
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def load_modelRE(tokenizer):
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model_re = AutoModelForSequenceClassification.from_pretrained("dexay/reDs3others", )
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return pipeline("text-classification", tokenizer = tokenizer,model=model_re, )
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