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import spacy_streamlit
import streamlit as st
import typer
from scripts.torch_ner_model import build_torch_ner_model
from scripts.torch_ner_pipe import make_torch_entity_recognizer
def main(models: str = None, default_text: str = None):
models = "training_trf/model-best"
test = "The patient had surgery."
models = [name.strip() for name in models.split(",")]
labels = ["person", "problem", "pronoun", "test", "treatment"]
spacy_streamlit.visualize(
models, default_text, visualizers=["ner"], ner_labels=labels
)
st.title('NER Predictor')
st.header('Enter the characteristics of the diamond:')
if __name__ == "__main__":
try:
typer.run(main)
except SystemExit:
pass
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