Update app.py
Browse files
app.py
CHANGED
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@@ -27,9 +27,9 @@ ENTITY_COLORS = {
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MAP_MODELS = {
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"":"",
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"fr_ner4archives_V3_camembert_base": "https://huggingface.co/ner4archives/fr_ner4archives_V3_camembert_base/resolve/main/fr_ner4archives_V3_camembert_base-any-py3-none-any.whl
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"fr_ner4archives_v3_default": "https://huggingface.co/ner4archives/fr_ner4archives_v3_default/resolve/main/fr_ner4archives_v3_default-any-py3-none-any.whl
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"fr_ner4archives_v3_with_vectors":"https://huggingface.co/ner4archives/fr_ner4archives_v3_with_vectors/resolve/main/fr_ner4archives_v3_with_vectors-any-py3-none-any.whl
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}
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@@ -147,7 +147,7 @@ def main():
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model_loaded = None
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if model != "":
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try:
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-
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flag_model = True
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streamlit.write(f"{model} is available locally.")
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except:
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@@ -160,7 +160,6 @@ def main():
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o = p1.wait()
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if o == 0:
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streamlit.write(f"Download model: {model} done.")
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model_loaded = spacy.load(model)
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flag_model = True
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streamlit.write(f"{model} is available locally.")
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placeholder.empty()
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@@ -193,7 +192,7 @@ def main():
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if streamlit.button('Launch'):
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plain = "\n".join(sentences)
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with streamlit.spinner('Initialize NER...'):
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nlp =
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nlp.max_length = 5000000
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if linking:
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nlp.add_pipe('entityfishing',
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MAP_MODELS = {
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"":"",
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"fr_ner4archives_V3_camembert_base": "https://huggingface.co/ner4archives/fr_ner4archives_V3_camembert_base/resolve/main/fr_ner4archives_V3_camembert_base-any-py3-none-any.whl",
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"fr_ner4archives_v3_default": "https://huggingface.co/ner4archives/fr_ner4archives_v3_default/resolve/main/fr_ner4archives_v3_default-any-py3-none-any.whl",
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"fr_ner4archives_v3_with_vectors":"https://huggingface.co/ner4archives/fr_ner4archives_v3_with_vectors/resolve/main/fr_ner4archives_v3_with_vectors-any-py3-none-any.whl"
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}
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model_loaded = None
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if model != "":
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try:
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spacy.load(model)
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flag_model = True
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streamlit.write(f"{model} is available locally.")
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except:
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o = p1.wait()
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if o == 0:
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streamlit.write(f"Download model: {model} done.")
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flag_model = True
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streamlit.write(f"{model} is available locally.")
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placeholder.empty()
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if streamlit.button('Launch'):
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plain = "\n".join(sentences)
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with streamlit.spinner('Initialize NER...'):
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nlp = spacy.load(model)
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nlp.max_length = 5000000
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if linking:
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nlp.add_pipe('entityfishing',
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